Systems and methods of efficiently performing biological assays

ABSTRACT

An automated laboratory system for processing biological samples in a batch type manner is disclosed. In one embodiment, the system may receive assay instructions for biological samples processing among a plurality of devices. The devices may include a pre-analytical instrument and one or more analysis systems. The system may include an orchestration core application for determining an order of performance for the assays ordered for the samples.

RELATED APPLICATIONS

The present application is a U.S. national phase application under 35U.S.C. § 371 of International Application No. PCT/US2018/064221, filedDec. 6, 2018 and published in English as WO 2019/113296 on Jun. 13,2019, which claims priority under 35 U.S.C. § 119(e) to U.S. ProvisionalApplication No. 62/596,052, filed on Dec. 7, 2017; U.S. ProvisionalApplication No. 62/596,032, filed on Dec. 7, 2017; and U.S. ProvisionalApplication No. 62/626,581, filed on Feb. 5, 2018. The content of eachof these related applications is incorporated herein by reference in itsentirety.

BACKGROUND Field

The present disclosure relates generally to the field of diagnosisautomation and more particularly automated orchestration of biologicalassays.

Description of the Related Art

Diagnostic testing of biological samples is instrumental in the healthcare industry's efforts to quickly and effectively diagnose and treatdisease. Clinical laboratories that perform such diagnostic testing mayreceive hundreds or thousands of samples on a daily basis with an everincreasing demand. The challenge of managing such large quantities ofsamples may be assisted by the automation of sample analysis. Automatedsample analysis is typically performed by automated analyzer instrumentsthat are commonly self-contained systems which perform multistepprocesses on the biological samples to obtain diagnostic results.

Automated clinical analyzer instruments offer a user an array ofautomated tests that may be performed on a provided sample. However,when samples arrive at the laboratory, they are often not ready foranalysis. In order to prepare a sample for testing with an automatedanalyzer instrument, a laboratory technician typically transfers analiquot of the sample from a primary container or tube, as received bythe laboratory, to a secondary container or tube which is amenable tothe analyzer instrument. In addition, the technician typically may needto know what tests are to be performed on the sample so that thetechnician may select a test-specific reagent or diluent to be pairedwith the sample. This may be time consuming and may lead to operatorerror and exposure to communicable diseases.

Pre-analytical instruments meant to help prepare a sample for analysisand further remove the technician from the orchestration between thelaboratory's receipt of a sample and the analyzer instrument's testresults also exist. However, many of these instruments still requiresignificant technician involvement, such as prior to loading samples inthe pre-analytical instrument, once the samples have been prepared bythe pre-analytical instrument, and once the analyzer instruments havecompleted analysis.

For example, some pre-analytical instruments may automatically transferan aliquot of a sample from a first container to a second container.However, such systems often require a technician to manually pairidentification codes of the first and second containers prior to loadingthem into the system, which may be time consuming and is prone to error.

In addition, many of these systems are not capable of being integratedwith one or more analyzer instruments. In this regard, a technician mayneed to be present to manually transfer the samples from thepre-analytical instrument to an analyzer instrument and from theanalyzer instrument to a storage location once analysis is complete.This redirects skilled labor to menial tasks and may create distractionsin that the technician must be ever mindful of the progress of thesamples within the pre-analytical instrument and analyzer instrument sothat the technician is prepared to transfer samples when ready in orderto minimize downtime.

Moreover, current pre-analytical instruments and analyzer instrumentsgenerally process samples in a continuous stream as they are introducedinto the system. Thus, such systems process samples in a predefinedsequence which is generally set by the user. In this regard, existingpre-analytical instruments generally do not take into accountinformation other than what is provided by the user when deciding whichsample to prepare next in the sequence. Furthermore, pre-analyticalinstruments typically prepare samples at different rates than theanalyzer instruments which further complicate the integration betweenpre-analytical instruments and analyzer instruments. In this regard, atechnician may be required to continuously keep track of samplesprepared by the pre-analytical instrument until a full batch of samplesis accumulated for manual transfer to an analyzer instrument.Alternatively, technicians may transfer partial batches to an analyzerinstrument, which may reduce the analyzer instrument's productivity.

SUMMARY

Disclosed herein are systems and methods for running assays onbiological samples and high throughput automation of biological assays.In one embodiment, the system comprises: a memory storing instructions;and a processor programmed by the instructions to execute a methodcomprising: receiving a plurality of assay instructions for a pluralityof biological samples; determining the plurality of assays that need tobe performed for each sample in the plurality of biological samplesbased on the assay instructions; determining the assay resources thatare available to perform the plurality of assays; determining an orderto perform each assay in the plurality of assays based on the assayresources that are available in order to maximize the efficiency ofperforming the plurality of assays; and instructing one or more analyzerinstruments to carry out the plurality of assays based on the determinedorder.

In one embodiment, the method comprises: receiving a plurality of assayinstructions for a plurality of biological samples; determining theplurality of assays that need to performed for each sample in theplurality of biological samples based on the assay instructions;determining the assay resources that are available to perform theplurality of assays; determining an order to perform each assay in theplurality of assays based on the assay resources that are available inorder to maximize the efficiency of performing the plurality of assays;and instructing one or more analyzer instruments to carry out theplurality of assays based on the determined order.

In one embodiment, the system comprises a memory storing instructions;and a processor programmed by the instructions to execute a methodcomprising: receiving a plurality of assay instructions for a pluralityof biological samples from a plurality of analysis systems; determiningthe plurality of assays that need to performed for each sample in theplurality of biological samples based on the assay instructions;identifying the analysis systems available to run each type of assay inthe plurality of assays; determining the assay resources within theidentified analysis systems that are available to perform the pluralityof assays; determining an order to perform each assay in the pluralityof assays based on the assay resources that are available in order tomaximize the efficiency of performing the plurality of assays; andinstructing one or more analysis systems to carry out specific assays ofthe plurality of assays based on the determined order.

In one embodiment, the system comprises: a first automated moduleconfigured to prepare a biological sample for at least one molecularassay; at least one second automated module for receiving the biologicalsample prepared by the first automated module and for performing amolecular assay on the received biological sample, wherein the firstautomated module and the second automated module each comprise at leastone automated instruments; and an orchestration core computing device incommunication with the first automated module, the second automatedmodule and a laboratory information system, wherein the orchestrationcore computing device receives instructions for processing biologicalsamples from the analysis system and manages the processing resources ofthe first and second automated devices where the orchestration corecomputing device comprises at least four processing layers, the firstlayer, which is in communication with the analysis system, being aservice level object layer, an orchestration layer, an instrument modulecontrol layer and an instruments module layer, wherein the instrumentsmodule layer is in communication with the automated instruments in thefirst and second automated devices, and wherein the state of theautomated instruments is communicated to the orchestration layer andbased on the current state of the analysis systems, the orchestrationcore computing device groups two or more biological samples into a batchand communicates instructions to the instrument module layer for batchprocessing the samples.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of an analysis system according to oneembodiment described herein.

FIG. 2A is a block diagram of a distributed analysis system incommunication with a laboratory information system according to oneembodiment described herein.

FIG. 2B is a block diagram of a centralized analysis system incommunication with a laboratory information system according to oneembodiment described herein.

FIG. 3A is a block diagram of an orchestration core computing devicearchitecture according to one embodiment described herein.

FIG. 3B is a block diagram of an orchestration core computing devicearchitecture according to another embodiment described herein.

FIG. 4 is a block diagram of components of an orchestration coreapplication according to one embodiment described herein.

FIG. 5A is a block diagram of an orchestration core application andorchestration sub-applications according to one embodiment describedherein.

FIG. 5B is a block diagram of an orchestration core application andorchestration sub-applications according to another embodiment describedherein.

FIG. 6 illustrates one embodiment of an orchestration core applicationdescribed herein.

FIG. 7 is a block diagram illustrating various instrument states for ananalysis system.

FIG. 8 is a block diagram illustrating various instrument states for ananalysis system.

FIG. 9 is a block diagram that illustrates exemplary assay states for ananalysis system.

FIG. 10 is a flow diagram of one exemplary method of determining anorder of performance of assays or assay steps for samples to maximizeperformance in an analysis system.

FIG. 11 is a block diagram of one example of determining an order ofperformance of assay steps for samples to maximize performance in ananalysis system.

FIG. 12 is a flow diagram of one exemplary method of determining anupdated order of performance of assays or assay steps after receiving anew assay instruction in an analysis system.

FIG. 13 is a flow diagram of one exemplary method of determining anorder of performance and an updated order of performance of assays orassay steps to maximize a performance metric.

FIG. 14 is a flow diagram of another exemplary method of determining anorder of performance and an updated order of performance of assays orassay steps to maximize a performance metric.

FIG. 15 is a block diagram of an orchestration core application incommunication with hospital and laboratory information systems andanalysis systems over a network.

FIG. 16 is a schematic illustration of a cloud server-basedorchestration core application in communication with an orchestrationlaboratory application to coordinate automated sample processing andanalysis.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe Figures, may be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein and made part of the disclosure herein.

Overview

The present disclosure describes devices, systems, and methods ofperforming processing and analysis of biological samples. In particular,a system architecture is described that coordinates automated sampleprocessing among a plurality of analysis devices or systems having ahigh degree of automation. Inputs from a laboratory information systemare received by an orchestration computing device that coordinates theoperation of one or more analyzer and pre-analytical instruments toprocess samples in an informed and efficient manner to increase theoverall efficiency of running assays on a plurality of analysis systemsand analyzer instruments (also referred to as analyzers and assaydevices). A variety of discrete inputs into the orchestration computingdevice are contemplated, the aggregate of inputs providing for efficientand expeditious sample processing with a minimum of operator inputs andinterventions.

Sample Processing and Analysis System

FIG. 1 depicts an exemplary analysis system 100. The analysis system 100can be an in vitro diagnostic system or include an in vitro diagnosticdevice. Such system, as depicted, includes a pre-analytical instrument104, a first analyzer instrument 108 a, and a second analyzer instrument108 b. The pre-analytical instrument 104 may include a user interface112 for receiving user inputs and an input window 116 for receivingsamples. Each of these units 104, 108 a, and 108 b is modular. Thus, thepre-analytical instrument 104 may be coupled to one or more analyzerinstruments. In addition, each analyzer instrument that is incommunication with the pre-analytical instrument 104 (both in terms ofexchanging information and samples for processing) may perform the sameor different operations. For example, the first analyzer instrument 108a may perform viral assays, such as human papilloma virus (“HPV”)assays, while the second analyzer instrument 108 b may perform bacterialand parasitic assays, such as those for detecting Chlamydia trachomatis,Neisseria gonorrhea, Trichomonas vaginalis, group B streptococcus,enteric bacteria, and enteric parasites. However, in some embodimentsthe analysis system 100 may be configured so that first and secondanalyzer instruments 108 a, 108 b are similar and capable of performingthe same or similar assays. Such instrument modularity allows a clinicallaboratory to tailor an analysis system 100 for its particular needs. Ananalysis system 100 is referred to herein as an electronic system.

The pre-analytical instrument 104 and analyzer instruments 108 a, 108 beach have hardware components that allow them to perform designatedoperations. For example, in one embodiment pre-analytical instrument 104may be configured to pre-process biological samples so as to prepare thesamples for analysis by the analyzer instruments 108 a, 108 b. In thisregard, the pre-analytical instrument 104 may have tray/shuttle handlingrobots that are capable of transporting trays/shuttles of samplecontainers from one location to another within the instrument and toadjacent analyzer instruments, sample container manipulation robots thatare capable of transporting and/or decapping individual samplecontainers, pipette robots that are capable of aspirating samples fromone container and into another container, diluent dispensers fordiluting samples, vortexers for vortexing samples, heat plates forwarming samples, and cooling units for cooling samples. The analyzerinstruments 108 a, 108 b may also have robotics that are capable ofmoving containers within their individual instruments, from thepre-analytical instrument 104, and back to the pre-analytical instrument104. The analyzer instruments 108 a, 108 b may also include pipetterobots, sample container manipulation robots, magnetic extractors (forproviding a magnetic field to the sample container that is used (inconjunction with paramagnetic particles added to the sample) for samplepurification), and any other hardware components that are needed forperforming instrument operations.

In addition to the hardware components, the pre-analytical instrument104 includes staging or accumulation areas. These areas are locations inwhich sample containers and other consumables are stored until they aredesignated for input into the workflow. These accumulation areas are incommunication with the orchestration core application so that theorchestration core application may assign processing information to thesample so that the instrument may process the sample according to theinstructions of the orchestration control application, as is describedfurther below.

FIG. 2A is a block diagram of an analysis system in communication with alaboratory information system according to one embodiment describedherein. In one embodiment, an analysis system 100 may include at leastone pre-analytical instrument 104 and one or more automated analyzerinstruments 108. The pre-analytical instrument 104 may process thesamples for analysis in the analyzer instruments 104. The analyzerinstruments 108 may be configured to perform assays on biologicalsamples while the pre-analytical instrument 104 may be configured toprepare samples for analysis by the analyzer instruments 108. Forexample, the pre-analytical instrument 104 may transfer a biologicalsample from one container to another container which is suitable for useby the analyzer instruments 108 and may also vortex, pre-warm, and coolthe samples depending on the assays to be performed. Such analyzerinstruments 108 and pre-analytical instrument 104 may each be modularstandalone units that have robotics capable of transferring biologicalsamples back and forth between the individual units when coupledtogether.

The analysis system 100 may be in communication with a laboratoryinformation system 204 over a network 208. The laboratory informationsystem 204 may be an existing information system that is operated by ahealthcare facility or standalone clinical laboratory. Such laboratoryinformation system may provide information regarding sample assayinstructions 212, requirements for the assays ordered 216, and patientinformation to the analysis system. In some implementations, theanalysis system 100 may receive patient information from a hospitalinformation system.

The analysis system 100 may include an orchestration core application220 executed by an orchestration core computing device 224 thatcommunicates with the analyzer instruments 108 and the pre-analyticalinstrument 104 through a cross instrument interface 228, and thelaboratory information system 204 through the network 208. The analysissystem 100 may be behind a firewall or connect to the network 208through another computing system to isolate the analysis system 100 andprotect it from any incidental or malicious software that could impedeor alter the performance of the analysis system 100.

The orchestration core application 220 may coordinate processes andmanage resources among the one or more analyzer instruments 108 and thepre-analytical instrument 104 in order to achieve efficient uses of theavailable resources and keep the activity of those resources at or abovea predetermined threshold level. The performance of the analysis system100 may be determined based on a performance metric. For example, theperformance metric may be a percentage of the maximal use of theprocessing resources available for the processing requirements at agiven point in time. In addition, the orchestration core application 220leverages information received from the laboratory information system204, the analyzer instruments 108, and the pre-analytical instrument 104to reduce, significantly reduce, or even eliminate operator involvementand to make high level decisions regarding activities that are to takeplace within each instrument based on ever-changing circumstances.

In one implementation, the computing devices 232, 236 of thepre-analytical instrument 104 and analyzer instruments 108 executeorchestration sub-applications 240, 244. Such orchestrationsub-applications 240, 244 are linked to the orchestration coreapplication 220 for implementing instructions provided by theorchestration core application 224. In this regard, decisions andinstructions for implementing such decisions are communicated downwardfrom the orchestration core application 220 to specific hardwarecomponents that perform the instructed actions. The instructions becomemore specific as they move down the chain from the orchestration coreapplication to individual hardware devices. Information is alsocommunicated upward from the individual hardware devices to theorchestration core application so that the orchestration coreapplication frequently receives state updates which inform thedecision-making process.

The orchestration core application 220 and the orchestrationsub-applications 240, 244 may include state machines that operate ontheir own threads. In this regard, the core application 220 and thesub-applications 240, 244 may have lock down states that are used tomake decisions so that a change in state does not interfere with thedecision making process.

The orchestration core application 220 and orchestrationsub-applications 240, 244 operate to achieve efficient use of theanalytical instruments 108 and pre-analytical instrument 104. The goalis to obtain desired utilization of hardware resources within suchinstruments because idle time of system resources detracts from overallperformance.

The orchestration core application 220 makes decisions based on theinformation from the laboratory information systems 204 regarding thebiological samples that are to be processed and evaluated by thepre-analytical and analytical instruments 104, 108, respectively. Theorchestration core application 220 organizes the individual biologicalsamples into batches within the pre-analytical instrument 104, whichhelps maximize overall throughput. Samples are placed into a batch basedon identity of processing conditions (e.g. thermocycling conditions) forthe samples in the batch. To the extent possible, each sample in a batchis subjected to the same processing conditions (e.g. temperature, lightfrequencies). However, processing uniformity is not required. Forexample, if sample or control containers in a batch have already beenpre-warmed, those samples will not be subjected to a pre-warming step.So not only is information about an individual sample “tracked” by theorchestration core application 220, information about the batch withwhich the individual sample is processed is also tracked. Said anotherway, there is a “one-to-many” relationship between the batch and thesamples. Some information is specific to the samples and otherinformation applies to each sample in the batch across the board.

In addition to implementing batch processing of samples, theorchestration core application 220 obtains a wide array of informationinputs from a variety of sources in controlling and coordinating theprocessing resources 248, 252 of the pre-analytical and analyticalinstruments 104, 108. Such information includes the inventories ofconsumables 256, 260 for the instruments and the allocation of thatinventory for the processes in queue, operational state of theinstrument hardware, the assays ordered to be performed on the samples,sample availability; batches already in process, sample age,availability of the pre-analytical and analytical instruments 104, 108,availability of the instrument devices 264, 268 of the pre-analyticaland analytical instruments 104, 108, biochemical stability of samplesand reagents 272, 276, and the particular laboratory's business orcompliance practices. The pre-analytical and analytical instruments 104,108 are also referred to herein as instrument devices. In oneembodiment, the analysis system 100 includes redundant hardware andconsumables such that the analysis system 100 may keep operating whilehardware is replaced and consumables are being replenished.

The orchestration core application 220 receives the assay instructionsfrom a variety of different external systems such as the laboratoryinformation system 204, a hospital information system, and anotheranalysis system. In some implementations, the pre-analytical instrument104 knows precisely what to do with the sample when it arrives in thepre-analytical instrument 104. Decisions regarding the actual processingmay be largely pre-made. That is, decisions about batching, timing,assay and consumable resources required will all be factored in to theorchestration core application 220 by the time the sample arrives at thepre-analytical instrument.

The orchestration core application 220 may include three components: anorchestration state component, an orchestration decider component and anorchestration engine component. Each component has a distinct, assignedrole in managing resources and controlling operation of thepre-analytical and analytical instrument devices 264, 268. Theorchestration state component stores state information. Theorchestration state component is configured to receive the operationalstate of the system hardware and instrument devices 264, 268. Thereforeeach instrument and submodule within each instrument is configured tocommunicate out information about its state and that state informationis communicated to the orchestration state module either directly but,more typically, through the logic of the applicable instrument. Theorchestration decider component uses the state information to makedecisions. The orchestration engine component implements the decisionsand guards the orchestration state component from being updated while adecision is being made.

In this regard, the orchestration core application 220 tracks consumableinventory. It is also configured to determine how much of the consumablequantity is allocated to batches being processed. Using suchinformation, the orchestration core application 220 is configured todetermine a net consumable inventory and make process flowdeterminations based upon the net amount of inventory to ensure samplesare not process without consumable availability. In addition, theorchestration core application 220 is configured to notify a user thatcertain consumables need to be replenished in an instrument. Suchconsumables 256, 260 may include diluent, reagents, assay controlsamples, pipette tips, empty sample containers, extraction containers,and PCR plates, to name a few. Various sensors may be implemented totrack such consumables 256, 260, such as a liquid level sensor for bulkdiluent. Also, the orchestration core application 220 may keep track ofa starting consumable inventory and how much of the consumables 256, 260have been used from the start consumable inventor to determine a netvalue.

The orchestration core application 220 also tracks operational states ofthe analyzer instruments 108 and pre-analytical instrument 104themselves. The orchestration core application 220 makes decisions onwhat samples may be processed and when the processing should start basedon this information. The instrument devices 264, 268 may includephysical hardware components such as motor encoders, integratedcircuits, solenoids, and the like which help the orchestration coreapplication 220 track the operational state of the hardware in eachinstrument. One aspect of an operational state is whether or not thereis a failure or error in the operation of a particular component. Insuch event, the orchestration core application 220 is aware of redundantdevices in the system and coordinates or activates such redundantdevices in the event of component operational errors or failures. Inthis regard the orchestration core application 220 has pre-determinederror protocols that it will execute in the event of a componentoperational error or failure. Another function performed by theorchestration core application 220 is to both understand theinstruments, devices and individual components necessary to process agiven batch and whether or not the hardware components, pre-analyticalinstruments, and analyzer instrument are currently engaged in or areallocated to a process.

The orchestration core application 220 communicates with one or moreinformation systems to acquire sample assay instructions 212. Suchsystems may include hospital information systems, laboratory informationsystems 204, informatics systems and another analysis system. Theorchestration core application 220 is configured to obtain thisinformation as early as possible so that decisions about sampleprocessing are made before the sample is actually scanned into thepre-analytical instrument 104. In this regard, a laboratory techniciandoes not need to acquire sample assay order information, which reducesuser error and frees the technician for other tasks.

The orchestration core application 220 is also configured to track thebiological/chemical/mechanical lifetime of consumable inventory andsamples, such as assay controls and reagents, and the biological samplesthemselves in various states of an assay protocol's execution. Exceedinglimits of useful lifetime of samples and consumables may adverselyaffect the integrity of the assay results. Such lifetimes decrease astime advances and, if the age of a reagent or a sample exceeds aparticular threshold, then the biochemistry of these reagents or samplesmay be altered. The orchestration core application 220 may prioritizesamples in such a way that completion of assay protocol steps prior to areagent or sample exceeding its lifetime is ensured.

The orchestration core application 220 may be further configured toreceive information from the pre-analytical and analytical systems 104,108 that will permit tracking the samples throughout their processing.This includes tracking sample aliquots obtained and dispensed todifferent containers for sample processing and sample transport from oneinstrument to another, such as sample transport from the pre-analyticalinstrument 104 to the analyzer instrument 108 (and back). This allows alaboratory technician to query the systems and instruments for samplelocation and its assay progress. If multiple assays are ordered for asingle patient sample, the orchestration core application 220coordinates and tracks execution of the multiple assays for the singlesample without user intervention to maximize, or at least increase, theoverall efficiency of carrying out the assays.

FIG. 2B is a block diagram of a centralized analysis system 100 b incommunication with a laboratory information system according to oneembodiment described herein. The analysis system 100 b in FIG. 2B issimilar to the analysis system 100 described with reference to FIG. 2A.As described in further details below, the analysis system 100 b in FIG.2B is a centralized system with the functions of the orchestrationsub-applications 240 b, 244 b performed by the orchestration corecomputing device 224 b.

In one embodiment, the analysis system 100 b may include at least onepre-analytical instrument 104 b and one or more automated analyzerinstruments 108 b. The pre-analytical instrument 104 b may process thesamples for analysis in the analyzer instruments 104 b. The analyzerinstruments 108 b may be configured to perform assays on biologicalsamples while the pre-analytical instrument 104 b may be configured toprepare samples for analysis by the analyzer instruments 108 b. Theanalysis system 100 b may be in communication with a laboratoryinformation system 204 b over a network 208 b. The analysis system 100 bmay include an orchestration core application 220 b executed by anorchestration core computing device 224 b that communicates with theanalyzer instruments 108 b and the pre-analytical instrument 104 bthrough an interface 228 b, such as a cross instrument interface, aninter-device interface, or an intra-device interface. The analysissystem 100 b may communicate with the laboratory information system 204b through the network 208 b. The orchestration core application 220 bmay coordinate processes and manage resources among the one or moreanalyzer instruments 108 b and the pre-analytical instrument 104 b inorder to achieve efficient uses of the available resources and keep theactivity of those resources at or above a predetermined threshold level.

The orchestration core computing device 224 b executes orchestrationsub-applications 240 b, 244 b. Such orchestration sub-applications 240b, 244 b are linked to the orchestration core application 220 b forimplementing instructions provided by the orchestration core application220 b. In this regard, decisions and instructions for implementing suchdecisions are communicated downward from the orchestration coreapplication 220 b to the orchestration sub-applications 240 b, 244 b tothe specific hardware components that perform the instructed actions.The instructions become more specific as they move down the chain fromthe orchestration core application 220 b to the orchestrationsub-applications 240 b, 244 b to the individual hardware devices.Information is also communicated upward from the individual hardwaredevices to the orchestration core sub-applications 240 b, 244 b to theorchestration core application 220 b so that the orchestration coreapplication 224 b and sub-applications 240 b, 244 b frequently receivesstate updates which inform the decision-making process.

The orchestration core application 220 b and orchestrationsub-applications 240 b, 244 b operate to achieve efficient use of theanalytical instruments 108 b and pre-analytical instrument 104 b. Theorchestration core application 220 b makes decisions based on theinformation from the laboratory information systems 204 b regarding thebiological samples that are to be processed and evaluated by thepre-analytical and analytical instruments 104 b, 108 b, respectively. Inaddition to implementing batch processing of samples, the orchestrationcore application 220 b obtains a wide array of information inputs from avariety of sources in controlling and coordinating the processingresources 248 b, 252 b of the pre-analytical and analytical instruments104 b, 108 b. The orchestration core application 220 b receives theassay instructions from a variety of different external systems such asthe laboratory information system 204 b, a hospital information system,and another analysis system.

The orchestration core application 220 b may include three components:an orchestration state component, an orchestration decider component andan orchestration engine component. The orchestration core application220 b may track consumable inventory. The orchestration core application220 b also tracks operational states of the analyzer instruments 108 band pre-analytical instrument 104 b themselves. The orchestration coreapplication 220 b is also configured to track thebiological/chemical/mechanical lifetime of consumable inventory andsamples, such as assay controls and reagents, and the biological samplesthemselves in various states of an assay protocol's execution. Theorchestration core application 220 b may be further configured toreceive information from the pre-analytical and analytical systems 104b, 108 b, via orchestration sub-applications 240 b, 244 b that willpermit tracking the samples throughout their processing.

In the embodiment shown in FIG. 2B, the orchestration core application220 b, orchestration sub-application 240 b, and orchestrationsub-application 244 b are illustrated as three components of theorchestration core computing device 224 b. However, this is illustrativeonly and is not intended to be limiting. In another embodiment, theorchestration core computing device 224 b may implement an orchestrationcore application 220 b may perform the functionalities of theorchestration sub-applications 240 b, 244 b. In one embodiment, theorchestration core computing device 224 b includes one orchestrationsub-application that is linked to the orchestration core application 220b for implementing instructions provided by the orchestration coreapplication 220 b.

Orchestration Core System Architecture

FIG. 3A depicts an orchestration core computing device architecture 300that supports the analysis system 100, such as the analysis system 100described with reference to FIG. 2A, according to an embodiment of thepresent disclosure. Architecture generally includes an orchestrationcore computing device 224 with a user interface, such as the userinterface 112, to allow a user to communicate therewith. Theorchestration core computing device 224 may include one or more codescanners 304 for reading sample identifiers (e.g., barcodes, QR codes)on sample containers or sample racks. The orchestration core computingdevice 224 is in communication with a pre-analytical instrument computercontrol device 232 of the pre-analytical instrument 104, and one or moreanalyzer computer control devices 236 a 1, 236 a 2 (illustrated here astwo such control devices; one for each analyzer instrument) of theanalytical instruments 108 a, 108 b. As shown, orchestration corecomputing device 224 is connected to a network 208, which is alsoconnected to a laboratory information system 204 (“LIS”). The LIS 204may be an existing generic or customized system associated with adiagnostic laboratory or medical facility that stores and maintainspatient records, physician ordered assays, etc., among other things. Thenetwork 208 allows orchestration computer core computing device 224 tobe communicatively coupled with the LIS 204 and share informationtherebetween.

Orchestration core computing device 224 is also communicatively coupledto instrument control devices 232, 236 a 1, and 236 a 2 of instruments104, 108 a and 108 b via a cross instrument interface 228. However,other interconnection mechanisms between the computer control devices232, 236 a 1, and 236 a 2 and the orchestration core computing device224 that allow the devices to share information with the system arecontemplated.

Pre-analytical instrument computer control device 232, in addition tobeing connected to the cross instrument interface 228, is connected to amodule interface 308 which is connected to the pre-analytical instrumentdevices 264 of system 100, allowing computer control device 232 tocommunicate with the pre-analytical instrument devices 264. Thepre-analytical instrument computing device 232 includes an applicationstored on its memory which provides instructions to its processorinvolving control of the physical operations utilized in preparation andpreprocessing of samples within system 100. In this regard, theapplication via the processor of pre-analytical instrument computercontrol device 232 helps control each instrument/device withinpre-analytical instrument modules/devices 264.

Analyzer computer devices 236 a 1, 236 a 2 may also each include aprocessor and memory. Analyzer computing device 236 a 1, in addition tobeing connected to cross instrument interface 228, is connected to amodule interface 312 a 1 which is connected to analyzer devices 268 a ofan analyzer instrument Ai, allowing analyzer computer device 236 a 1 tocommunicate therewith. Analyzer computing device 236 a 1 includes anapplication stored on its memory which provides instructions to itsprocessor involving control of the physical operations utilized inanalysis of a sample provided to the analyzer instrument Ai via thesystem 100. In this regard, the analyzer computing device 236 a 1, viaits processor, helps control each instrument/device within the analyzerinstrument Ai. Analyzer computing device 236 a 2 is similarly configuredfor its respective analyzer instrument.

Thus, as shown in FIG. 3A, orchestration core computing device 224receives information from multiple inputs and distributes theinformation as needed. This allows the system 100 to be fully integratedwith one or more analyzer instruments and with an information sharingnetwork that allows the system 100 to smartly perform preparation andpreprocessing of multiple different samples contained in multipledifferent containers.

In another embodiment of architecture 300, pre-analytical instrumentcomputer device 232 or analyzer computing devices 236 a 1, 236 a 2 mayalso act as the orchestration core computing device 224.

Each of the devices 232, 236 a 1, 236 a 2, and the orchestration corecomputing device 224 and the LIS 204 are at different nodes of thenetwork 208 and capable of directly and indirectly communicating withone another. However, as depicted, orchestration core computing device224 generally operates as a control interface between the LIS 204 andcomputing devices 232, 236 a 1, 236 a 2 of the analyzer instruments 108a, 108 b and pre-analytical instruments 104. The computing devices 232,236 a 1, 236 a 2 and the orchestration core computing device 224 and LISwithin the network 208 may be interconnected using various protocols andsystems. The network 208 may utilize standard communications protocols,such as Ethernet and Wi-Fi, and protocols that are proprietary to one ormore companies, and various combinations of the foregoing. Thecommunication between the laboratory information system 204 and theanalysis system 100 may be via communication protocols, such ashypertext transfer protocol (HTTP) Although certain advantages areobtained when information is transmitted or received as noted above, thesystem described herein is not limited to any particular communicationprotocol.

FIG. 3B is a block diagram of an orchestration core computing devicearchitecture 300 b according to the embodiment described with referenceto FIG. 2B. The architecture 300 b of the orchestration core computingdevice in FIG. 3B is similar to the architecture 300 b of theorchestration core computing device described with reference to FIG. 3A.Because the analysis system 100 b in FIG. 2B is a distributed systemwith the functions of the orchestration sub-applications 240 b, 244 bperformed by the orchestration core computing device 224 b, not thepre-analytical instrument 104 b and analytical instrument 108 b, theorchestration core computing device 224 b communicates with and/orcontrols the pre-analytical instrument devices 264 b and analyticalinstrument devices 268 b 1, 268 b 2 via an interface 228 b, such as across instrument interface, an inter-device interface, or anintra-device interface.

Orchestration Core Application and Sub-Applications States

FIG. 4 illustrates states of the orchestration core application orsub-applications. FIG. 4 illustrates multiple communication interfaces404 a-404 c in bidirectional communication with the cross instrumentinterface 228. These communication interfaces each have a processor.These interfaces 404 a-404 c are processors through which the operationsin each of the analytical 236 a 1, 236 a 2 and pre-analytical 232systems are coordinated with the orchestration core computing device224. Each of the communication interfaces 404 a-404 c is for eitheranalyzer computing device 236 a 1, 236 a 2, or pre-analytical computercontrol device 232. In this regard, each computing device in 404 a-404 ccontains one or more processors, memory and other components typicallypresent in general purpose computing devices.

The communication interfaces 404 a-404 c forward information regardingstate changes in the analytical and pre-analytical instruments to anorchestration state component 408 that is part of the pre-analyticalinstrument computing device 232 or one of the analyzer computing devices236 a 1 or 236 a 2. The orchestration state component 408 communicateschanges in state to the orchestration engine component 412 of thepre-analytical instrument computing device 232 or one of the analyzercomputing devices 236 a 1 or 236 a 2. The orchestration engine component412 is in bidirectional communication with the orchestration decidercomponent 416 of the pre-analytical instrument computing device 232 orone of the analyzer computing devices 236 a 1 or 236 a 2. In response torequests from the orchestration engine component 412, the orchestrationdecider component 416 determines whether or not the orchestration enginecomponent 412 is to dispatch instructions to the analytical andpre-analytical devices 108, 104.

Memory of each of the communication interfaces 404 a-404 c may storeinformation accessible by the one or more processors, includinginstructions that may be executed by the one or more processors. Theorchestration engine thread described above will execute on anyavailable processor core in the communication interfaces 404 a-404 c. Asnoted above, the orchestration engine component 412 requests a decisionfrom the orchestration decider component 416. If a decision is returned,the orchestration engine component 412 dispatches the action to theappropriate communication interface 404 a-404 c. When a communicationinterface 404 a-404 c receives a message involving state, it acquiresthe state from the orchestration engine component 412 and updates theorchestration state component 408 with its new state. The neworchestration state in the orchestration state component 408 thentriggers the orchestration engine component 412 to run.

Memory includes data that may be retrieved, manipulated or stored by theprocessor. The memory may be of any non-transitory type capable ofstoring information accessible by the processor, such as a hard-drive,memory card, ROM, RAM, DVD, CD-ROM, write-capable, and read-onlymemories.

The instructions may be any set of instructions to be executed directly,such as machine code, or indirectly, such as scripts, by the one or moreprocessors. In that regard, the terms “instructions,” “application,”“steps,” and “programs” may be used interchangeably herein. Theinstructions may be stored in object code format for direct processingby a processor, or in any other computing device language includingscripts or collections of independent source code modules that areinterpreted on demand or compiled in advance. Functions, methods, androutines of the instructions are explained in more detail below.

Data may be retrieved, stored or modified by the one or more processorsin accordance with the instructions. For instance, although the subjectmatter described herein is not limited by any particular data structure,the data may be stored in computer registers, in a relational databaseas a table having many different fields and records, or XML documents.The data may also be formatted in any computing device-readable formatsuch as, but not limited to, binary values, ASCII or Unicode. Moreover,data may comprise any information sufficient to identify the relevantinformation, such as numbers, descriptive text, proprietary codes,pointers, references to data stored in other memories such as at othernetwork locations, or information that is used by a function tocalculate the relevant data.

The one or more processors implemented by each of communicationinterfaces 232, 236 a 1, and 236 a 2 may be any conventional processors,such as a commercially available CPU. Alternatively, the processors maybe dedicated components such as an application specific integratedcircuit (“ASIC”) or other hardware-based processor.

In some embodiments, the processor or memory may actually comprisemultiple processors and/or memories that may or may not be stored withinthe same physical housing. For example, the memory may be a hard driveor other storage media located in housings different from that ofprocessor. Accordingly, references to a processor, computing device, ormemory will be understood to include references to a collection ofprocessors, computing devices, or memories that may or may not operatein parallel.

In the embodiment depicted in FIG. 2A, the analyzer computing devices236 a 1, 236 a 2 and pre-analytical computing device 232 are locatedwithin their respective instruments. The location of the orchestrationcore computing device 224 is largely a matter of design choice. As shownin the orchestration core computing device 224 may also be incommunication with a code scanner 304 and a user interface 112 ofpre-analytical instrument 104 (FIG. 2A). The code scanner 304 is locatedwithin an input window 116 of pre-analytical instrument 104. In oneembodiment, the user interface 112 is a touch screen device mounted tothe outer shell of the pre-analytical instrument 104 (shown in FIG. 2A).However, it should be understood that user interface 112 may comprise amobile device capable of wirelessly connecting to orchestration corecomputing device 224 wirelessly, such as via a Wi-Fi connection, forexample. By way of example only, user interface 112 may be a mobilephone or a device such as a wireless-enabled PDA, a tablet PC, or anetbook that is capable of obtaining information via the network 208. Inanother example, orchestration device computing device 224 may be adesktop device located in a physical location remote from the analysissystem 100.

Orchestration Core Application

As illustrated in FIG. 4 , an orchestration core application 220includes components for information flow such as communicationinterfaces 404 a-404 c, an orchestration decider component 416, anorchestration engine component 412, and an orchestration state component408. The orchestration state component 408 receives and holds allinformation regarding the orchestration state (i.e., the states ofsample processing and analysis for the system 100 that includes thepre-analytical and analytical systems). The orchestration decidercomponent 416 implements an algorithm that determines next actions to betaken based on the orchestration state received from the orchestrationstate component 408. The communication interfaces 404 a-404 c are taskedwith processing incoming information from analyzer instruments andpre-analytical instrument that is used to update the orchestrationstate.

The orchestration engine component 412 provides guarded access to theorchestration state, operates the orchestration decider component 416,and executes the decisions made by the orchestration decider component416 in the form of instructions that are distributed to computingdevices 232, 236 a 1, and 236 a 2. As previously mentioned,orchestration core application 220 is a state machine. Thus, statechanges that occur during a decision making process invalidate thedecision. The orchestration engine component 412 provides the guardedaccess to orchestration state component 408 while decisions are made sothat the decisions made by orchestration core application 220 are atomicdecisions (i.e. one decision at a time).

In one embodiment, in order to ensure such decisions are atomic, theorchestration engine component 412 runs on its own thread and isconfigured to implement one or more strategies for preventing stateupdates during a decision making process. In other embodiments, thethread is not configurable on the fly. For example, in one embodiment,the orchestration engine component 412 is configured to lock theorchestration state while a copy of the orchestration state is made.Such copy of the orchestration state is used in the decision makingprocess. This allows the lock on the orchestration state to be appliedfor a short period of time limiting the opportunity for a race conditionRace conditions may occur when multiple pieces of state data changeduring execution of a decision. For example at the start of the decisionthere is one batch and thirty patient samples, and at the end ofdecisions there are two batches and sixty samples. Both of these statesare consistent. If the orchestration state is not controlled by theorchestration engine component 412 could see the inconsistent state ofone batch and sixty samples, and therefore make an “invalidate”decision.

In another embodiment, the orchestration engine component 412 may beconfigured to first determine what action to perform, and then executethe action. Additionally, the orchestration engine component 412 may beconfigured to apply a lock to the orchestration state during thedecision making process. This may also allow the lock to be applied fora short period of time provided the decision regarding which action toperform is quick. Delayed decisions may delay processing and a delayeddecision may stop the state from being updated.

In a further embodiment, all state changes are automatically enteredinto a queue. The orchestration engine component 412 may be configuredto wake from a waiting condition, such as exiting a waiting or sleepstate, and process each of the changes in the queue. Once the queue isempty, the orchestration engine component 412 may be configured to thenrun the orchestration decider component 416 and execute the decisions.

In another embodiment, the orchestration core application 220, which maybe implemented by the orchestration core computing device 224, isconfigured to apply a lock over the orchestration engine component 412and orchestration state component 408. The lock is freed if theorchestration engine component 412 is in a waiting condition, whichindicates all activities associated with the locked-down state arecompleted. In this embodiment the lock is held for a longer time and mayprevent other threads from executing if the orchestration enginecomponent 412 is busy. Because of the longer lock, a race condition ismore likely.

Orchestration Sub-Application System

As depicted in FIG. 5A, analyzer instruments 108 a 1 and 108 a 2 andpre-analytical instrument 104 include orchestration sub-applications240, 244 a 1, 244 a 2. These applications 240, 244 a 1, and 244 a 2 arestored on the respective memories of the computing devices 232, 236 a 1,and 236 a 2 and provide instructions to their respective processorsinvolving the coordination and control of the hardware devices withinunits 104, 108 a 1 and 108 a 2, such as the hardware devices describedabove. The orchestration sub-systems 240, 244 a 1, and 244 a 2 are thecommunication link between the orchestration core application 220 andindividual components/subsystems/hardware within instruments 104, 108 a1 and 108 a 2. In this regard, sub-applications 240, 244 a 1, and 244 a2 assist in executing instructions provided by orchestration coreapplication 220 and allow for the modularity of each instrument 104, 108a 1 and 108 a 2. Thus, as shown, instructions flow from theorchestration core application 220 to the individual devices of theinstruments 104, 108 a 1 and 108 a 2. Such general instructionstranslate into targeted actions by discrete devices through programmingby delegation of authority as the instructions are communicated in adirection toward the hardware devices. For example, when thepre-analytical instrument 104 receives a rack of samples, one or more ofthe orchestration sub-applications 240 issue specific instructions tospecific devices 264 to accomplish the tasks necessary in support ofreceiving the rack of samples into the pre-analytical instrument 104. Inthis regard, information flows from the individual devices 264 to theorchestration core application 220. Such information may includeoperational states of the devices 264, current levels of consumables andlocations of particular samples. This pyramid structure allowsorchestration core application 220 to focus on high-level decisions andinformation gathering.

The orchestration sub-applications 240, 244 a 1, and 244 a 2 may beconfigured similarly to the orchestration core application 220 tocoordinate activities amongst the various devices within each unit 104,108 a 1, 108 a 2 and also across the units, 104, 108 a 1, 108 a 2. Forexample, a conveyor manager sub-application of pre-analytical instrument104 and a robotic arm manager sub-application of the second analyzerinstrument 108 a 2 may coordinate the availability and operation of arespective conveyor and robotic arm so as to hand-off sample containersfrom the conveyor of the pre-analytical instrument 104 to the roboticarm of the analyzer instrument 108 a 2.

In addition, the sub-applications 240, 244 a 1, 244 a 2 may be statemachines that operate on their own threads. For example, pre-analyticalinstrument 104 may have a rack manager sub-application that is a statemachine operating on its own thread. The rack manager sub-applicationmay be responsible for coordinating activities that move a rack ofsamples throughout the pre-analytical instrument 104. For example, rackmanager sub-application may hold rack objects and make decisions basedupon a rack state value assigned to the object, which may be a singleenumeration that indicates where the rack is and what operation is beingperformed on it. Such decisions may include which rack of samples tomove and where it will be moved to. In addition, the rack managersub-application coordinates the hand-off of a rack with other componentsor stations within pre-analytical instrument 104, such as a sampleconversion station or a rack elevator.

However, because the rack manager sub-application is a state machine,state changes that occur during a decision making process invalidate thedecision. In order to ensure such decisions are atomic, the rack managersub-application is configured to implement one or more strategies forpreventing state updates during a decision making process. For example,in one embodiment, rack manager sub-application may be configured toapply a lock to the rack states while a copy of the rack states is made.Such copy would be used in the decision making process. This would allowthe lock to be applied for a short period of time limiting theopportunity for a race condition.

FIG. 5B is a block diagram of an orchestration core application andorchestration sub-applications of the centralized analysis systemdescribed with reference to FIGS. 2B and 3B. As depicted in FIG. 5B, theorchestration sub-systems 240 b, 244 b 1, and 244 b 2 are thecommunication link between the orchestration core application 220 b andindividual components/subsystems/hardware within instruments 104 b, 108b 1 and 108 b 2. The orchestration sub-applications 240 b, 244 b 1, and244 b 2 may be configured similarly to the orchestration coreapplication 220 b to coordinate activities amongst the various deviceswithin each unit 104 b, 108 b 1, 108 b 2 and also across the units, 104b, 108 b 1, 108 b 2. The sub-applications 240 b, 244 b 1, 244 b 2 may bestate machines that operate on their own threads. The core application220 b may be a state machine that operates on its own thread.

Multi-Layer Orchestration Core Application Architecture

FIG. 6 illustrates an architecture for the orchestration coreapplication 220 which, as illustrated, has a multi-instrument servicelayer 610, an orchestration layer 620, and an instrument module layer630. Each layer is assembled from a plurality of system user objects,each encapsulating a separate user operational category. The pluralityof system user objects advantageously include (1) a service level object610 layer that includes the module service base module 614 for thesystem illustrated in FIG. 6 . The service level object layer 610 ispart of the orchestration control application service module 612 whichis in communication with the orchestration layer 620, the instrumentmodule control layer 630, and modules in the instruments module layer650. The orchestration control application service module 612 is incommunication with the module that requests sample information 646, themodule that coordinates batches 642 the module that manages moduleregistration 636 and the module that updates inventory status 632. Theorchestration control application service module 612 also communicateswith other modules in its layer (i.e. the module service base module 614and, through the module service base module 614, the service base module616).

In one embodiment, the orchestration engine module (or component) 624communicates with the module service base module 614 that also receivesinstructions from the orchestration control application service module612. The orchestration engine module 624 acquires orchestration statesfrom the orchestration state module 622. The orchestration state module622 receives state information from every module in the layer 630 and,indirectly, every module in the layer 650. These modules are theinventory state updater module 632, the available consumables per assaymodule 634, the module registration manager 636, the module state module638, the batch module 540, the coordinate batches module 642, the samplemodule 644 and the request sample information module 646. In response torequests from the orchestration engine module 624, the orchestrationdecider module 626 determines whether or not the orchestration enginemodule 624 is to dispatch instructions to other modules.

The request sample information module 646 communicates with theinstrument registration module 658 to provide instructions and obtaininformation regarding the registration and tracking of individualsamples in the instrument. In one embodiment the sample information isobtained by reading the sample code on the sample container received bythe instrument. The sample code on the transfer container is alsoregistered to identify and track the transfer containers in theinstrument. Note that the orchestration control application servicemodule 612 initiates the sample information request from the requestsample module 646 which causes the instrument registration module 658 toobtain the information about the sample containers and transfercontainers. Once the sample information is obtained, the sampleinformation in the sample information module 644 is updated. The updatedsample information is communicated to the orchestration state module622.

Layer 630 also has a module 642 that coordinates batches bycommunicating with the instrument coordinate batches module 656 in theinstrument. Through the interface with the coordinate batch module inlayer 630, the instrument coordinate batches module 656 populatesshuttles with samples designated by the orchestration controlapplication service module 612 to be in the same batch. The coordinatebatch module 642 also provides instructions to the instrument coordinatebatches module 656 to start the batch handler apparatus in theinstrument coordinate batches module 656 and for the instrumentcoordinate batches module 656 to start shuttle transfers. The coordinatebatch module 642 communicates with both the orchestration state module622 and the batch module 640 (which in turn communicate with theorchestration state module 622).

Layer 630 also has a module 640 that communicates the module state tothe orchestration state module 622. The module state module 638 acquiresinformation from the module registration manager 636 which receivesinstructions and direction from the orchestration control applicationservice module 612 in layer 610. The module registration manager 636also communicates information to the orchestration state module 622.Based on instructions from the orchestration control application servicemodule 612, the module registration manager 636 communicates with theinstrument device registration module 654.

As noted above, the layer 630 has a module 632 that updates theinventory state. The inventory state module 632 receives instantiationinstructions from the orchestration control application service module612 and updates the orchestration state module 622 with any stateupdates. The inventory state update module 632 controls the inventorymodule 652 in the pre-analytical instrument to obtain a variety ofinformation about the state of consumables in the instrument. Thatinformation includes the inventory information on the availableconsumables; retrieving consumables as required; reserving consumables;restoring consumables; changing the inventory.

In another embodiment, a rack manager sub-application may be configuredto first determine actions to perform, and then execute such actions.Additionally, the rack manager-sub application may be configured toapply a lock to the rack states during the decision making process. Thismay also allow the lock to be applied for a short period of timeprovided the decision regarding which action to perform quickly made.

In a further embodiment, all rack state changes are automaticallyentered into a queue. The rack manager sub-application may be configuredto wake from a waiting condition and process each of the changes in thequeue. Once the queue is empty, the rack manager sub-application may beconfigured to execute the decisions.

In an even further embodiment, the rack manager sub-application may beconfigured to apply a lock over the rack manager sub-application. Thelock is freed if the rack manager sub-application is in a waitingcondition, which indicates all activities associated with thelocked-down rack states are completed.

Instrument and Assay States

In one embodiment, the instruments are provided with defined states. Forexample, the instrument states may be defined as illustrated in Table 1.

TABLE 1 State Definitions STATE DESCRIPTION Offline Busy The instrumentis not available for general scheduling or concurrent activity. It isexecuting a single offline activity. Offline Idle The instrument is notavailable for general scheduling or concurrent activity. Online Busy Theinstrument is online and performing one or more concurrent procedures.Online Idle The instrument is available for general scheduling andconcurrent activity. Paused Idle An online instrument is paused whileidle. No new procedures may be initiated while paused. Paused Busy Anonline instrument that is performing one or more concurrent activitiesis paused between steps. Execution of those activities continues afterthe instrument is resumed. No new procedures may be initiated duringpause. Power Off The instrument is powered down.

Referring to FIG. 7 and FIG. 8 , the commands that will change one stateto another are illustrated. For example, when an instrument is in thepower off state, a command to power on will change the state to “offlineidle.” The offline idle state may either change to “offline busy” whenan offline procedure (e.g. instrument service; software update, etc.) isexecuting, in which case the offline idle state is maintained untilafter the offline procedure is completed. If there is no offlineprocedure preventing the state from changing from offline idle to onlineidle, a command to bring the instrument online with change the state toonline idle. In the online idle state, the instrument may be instructedto initiate a procedure. Once completed, the instrument is returned tothe online idle state. If the instrument is paused during execution(paused busy), no new procedures may be initiated until the state isreturned to online busy and the procedure is completed. When theinstrument is in the online idle state, it will remain available toreceive commands for further activity unless it enters the pause idlestate, in which case no new procedures may be initiated or aninstruction is received to take the instrument offline.

The system also has defined assay states. In one embodiment, the assaymay have one of the states set forth in Table 2 below.

TABLE 2 Assay State Definitions STATE DESCRIPTION Not Allowed The assaymay not be performed on this machine because of region rules or labqualifications. Unqualified The assay is allowed to be performed on thismachine, but is not qualified for patient samples. Qualified Assay hadbeen qualified for use on this machine. Patient sample may be performedon this assay. New Version The machine is qualified to perform versionof the Available assay, but a new official version has been released.The lab has yet to qualify this version of the assay. The old version isstill performed for all new batches of the assay.

FIG. 9 illustrates how the state is stored for a particular assay. Ifthe assay state is “not allowed” then region rules for the assay areapplied, in which case the assay is provided with an “unqualified” statethat will allow the assay to be performed but the assay results will notbe patient qualified. To obtain qualification, the performed ischallenged. If the state is qualified, but a new version of the assayhas been released, the older version of the assay is performed until thenew version is qualified.

Determining an Assays or Assay Steps Order

The orchestration core application 220 may determine an order ofperformance of assays or assay steps based on the samples received, theassays ordered, and availabilities of resources 248, 252. FIG. 10 is ablock diagram of a non-limiting exemplary method 1000 of determining anorder of performance of assays or assay steps for samples to maximizeperformance. In one embodiment, the orchestration core application 220may implement the method 1000 or a part of the method 1000. Afterbeginning at a block 1004, the method 1000 receives scanned sample codesat a block 1008. For example, after a rack of samples in containersarrives at the input window 116 of the analysis system 100, the codescanner 304 of the analysis system 100 may scan sample identifiersaffixed to the containers of samples, such as barcodes and twodimensional codes. The method 1000 may receive scanned sample codes asthey are scanned by the scanner 304. At a decision block 1012, if thescanner 304 scans and receives additional sample codes, the method 1000may return to the block 1008 to receive more sample codes. Theadditional sample codes may be from the same rack of samples or anotherrack of samples received by the analysis system 100.

At the decision block 1012, if no additional sample code is scanned andreceived, the method 1000 may proceed to a block 1016, where the method1000 determines assays to perform for the samples received and scanned.For example, the method 1000 may receive assay instructions for thesamples received and scanned from a laboratory information system 204 ora hospital information system. The method 1000 may determine assays toperform for the samples based on the sample identities determined fromsample codes and the assay instructions. For example, a doctor may orderthree tests A, B, and C for a patient, and the container containing thepatient's sample may have a sample code 123456 affixed to it. After themethod 1000 receives the sample code 123456, the method 1000 maydetermine the identity of the sample (i.e., the patient's sample) anddetermine that the doctor has ordered or instructed three assays for thepatient.

The method 1000 proceeds to a decision block 1020, where the method 1000determines whether the condition of each sample satisfies therequirements of the one or more assays ordered for the sample. Thecondition of the sample may be the sample volume, the sample age, thesample quality (e.g., sample opacity). For example, the three assays A,B, and C ordered by the doctor for the patient require 1 ml, 5 ml, and10 ml respectively. However, the volume of the patient's sample, asdetermined by the pre-analytical instrument 104, may only be 15 ml.Thus, the volume of the patient's sample does not satisfy the totalrequirements of the three assays ordered because at the volume of thepatient's sample is sufficient for two assays only. If the sample doesnot satisfy the requirements of the one or more assays ordered, themethod 1000 proceeds to a block 1024, where the method 1000 notifies auser that the sample condition does not satisfy the requirements of theordered assays. For example, the orchestration core application 220 maydisplay an error message using the user interface 112 of the analysissystem 100. The method 1000 then ends at a block 1028.

In some implementations, the assay instruction for a sample may includea priority of the assays to be performed. The method 1000 may determinethe assays that should be performed on a sample, even though thecondition of the sample does not satisfy the requirements of all theassays ordered for the sample. For example, the assay instruction of thepatient's sample may indicate that the results of the assays A and B mayonly be interpreted together. The assay instruction may also indicatethat assay A is more important than assay C. Thus, the method 1000 mayproceed from block 1020 to perform assays A and B, and notify the userthat assay C will not be performed. In some implementations, the method1000 may display the possible assays that may be performed for thesample and request user input regarding the assays that should beperformed.

At the decision block 1020, if the sample condition satisfies therequirements of the assays ordered, the method 1000 proceeds to adecision block 1032, where the method 1000 determines whether theanalysis system 100, including the pre-analytical instrument 104 andanalyzer instrument 108, has sufficient resources to perform all theassays ordered. If the analysis system 100 does not contain sufficientresources, the method 1000 proceeds to the block 1024, where the user isnotified that the analysis system 100 does not include sufficientresources to perform the ordered assays. The method 1000 then proceedsto the block 1028, where the method 1000 ends. For example, thepre-analytical instrument 104 may need to pipette the patient's samplefrom the sample container into three smaller containers. However, thepre-analytical instrument 104 may be out of pipette tips or may onlyhave two smaller containers. The method 1000 may notify the user, viathe user interface 112, that the user needs to stock the pre-analyticalinstrument 104 with more pipette tips and containers.

Table 3 illustrates exemplary resources of the analysis system 100 thatmay require exclusive access such that each resource may only be usedfor the preparation or analysis of one sample or one batch of samples.Some of these resources may be initiated by the analysis system 100automatically. Some of these resources may require specific userinitiations or user actions, possibly after the analysis system 100provides a user with options for the user to choose. For example, a usermay initiate the emptying of a waste container of the analysis system100. As another example, during daily maintenance, the analysis system100 may pause until a user acknowledges that the extraction area hasbeen cleaned. Table 4 illustrates exemplary additional resources of theanalysis system 100.

TABLE 3 Resources of the Analysis System that may Require ExclusiveAccess Group Name Initiation Maintenance Daily User schedule or requestSample Conversion Rack in hotel Sample Pass-Through Rack in hotel SampleHPV Sample Batch Assembled batch State Change Software update Userscheduled State Change Pause Dory User request Racks Load Sample RacksRack in I/O bay Racks Unload completed racks User request ConsumablesStock Dory consumable drawer User request Consumables Empty Roz wasteUser request Interventions Stuck Tubes in shuttle Consumable failure

TABLE 4 Resources of the Analysis System Resource Name Module SideConcurrency Constituent Devices Constituent Resource Light bar AnalysisNA Shared Light bar system Console Orchestration NA Shared All-in-onedisplay core application Inventory Pre-analytical Any analysis SharedInventory robot robot instrument instrument Operator NA NA Shared Alogged in lab tech Deck Analysis Any analysis Reserved Conveyor, Gantryinstrument instrument robot, Gripper, Sealer, Shaker 1 & 2, Shuttletransporter, Tube restraint Reader 1 Analysis Any analysis ReservedReader 1 instrument instrument Consumable Analysis Any analysis ReservedConsumable drawer, drawer 1 instrument instrument extractor ConsumableAnalysis Any analysis Reserved Consumable drawer, drawer 2 instrumentinstrument extractor Tip drawer Analysis Any analysis Reserved Tipdrawer instrument instrument Trough 1 Analysis Any analysis Reservednone instrument instrument Top cabin Analysis Any analysis Reserved Topcabin doors Deck, Consumable instrument instrument Drawer 1-6, TipDrawer, Trough 1-2 Waste Analysis Any analysis Reserved Liquid, solidand instrument instrument plate waste Bottom Analysis Any analysisReserved Bottom cabin doors Waste cabin instrument instrument

In one implementation, the method 1000 may determine the combination ofassays that may be performed given the shortage of system resources andlet the user determine the assays that should be performed. In anotherimplementation, the assay instructions may include assay and samplepriorities such that the method 1000 may notify the user of the lack ofsystem resources and proceed from the decision block 1032 to perform theassays based on the assay and sample priorities.

At the decision block 1032, if the analysis system 100 containssufficient resources, the method 1000 proceeds to a block 1036, wherethe assay steps or the assays that the analysis system 100 may performconcurrently are determined. For example, if assays A and B ordered forthe patient requires heating at 65° C. and 95° C. respectively, and ifthe analyzer instrument 108 contains only one heat plate for heatingsamples, then these two steps may not be performed concurrently.However, if the analyzer instrument 108 contains two or more heatplates, then these two assay steps may be performed concurrently.

The method 1000 proceeds to a decision block 1040 to determine whetherthe assay instructions include any special instructions. For example, aspecial instruction may state that the assay instruction for aparticular patient is a rush instruction and has the highest priority.As another example, a special instruction may indicate that either twoassays are both performed or neither is performed (possibly because theresults of the assays for a patient need to be interpreted together). Ifthere is no special instruction, the method 1000 proceeds to a block1044 to determine an order of performance to maximize a performancemetric. The performance metric may be based on one or more factors suchas the time duration for performing all the assays, the energy used forperforming all the assays, and quality or accuracy of assay results. Theorder of performance may be affected by scheduled events. For example,scheduled events may be daily maintenance, scheduled firmware orsoftware updates, scheduled hardware upgrade, and scheduled poweroutage. The order of performance may be affected by the physical orlogical configurations of the components of the analysis system 100. Forexample, the order of performance may be affected by the physical orlocal configurations of the pre-analytical instrument 104, analyticalinstrument 108, and electronic instruments 264, 268. The order ofperformance may be affected by the types of sample containers or otheridentifying elements of the sample. For example, the containercontaining a sample received may not be preferred for a type of assayordered for the sample. The order of performance may include a step oftransferring the sample from the sample container received to a moreappropriate sample container. The method 1000 then ends at the block1028.

At the decision block 1040, if the assay instructions include a specialinstruction, the method 1000 may proceed to a block 1048 to determine anorder of performance of the assays to be performed with the specialinstruction prioritized while maximizing the performance metric. Forexample, if an assay order for a patient is a rush order, the method1000 may determine an order of performance that maximizes theperformance of the assays other than those of the assays for the rushinstruction. In some embodiments, the performance of the assays isminimized unless all rush instructions are performed first. The method1000 then ends at the block 1028.

Example Order Determination

FIG. 11 is a schematic illustration of a non-limiting example ofdetermining an order of performance of assay steps for samples tomaximize performance. An analysis system 100 may include three resourcesA, B, and C. The three resources may be, for example, a vortexer, apipette, and a heat plate. Assays 1, 2, and 3 require the use of thethree resources in the order of A, B, and C, A, C, and B, and B, A, andC. To maximize performance, assay steps for different assays thatrequire the same resources may be batched together. FIG. 11 illustratesthree possible orders of performance of assay steps. As shown in FIG. 11, the order of performance (1) requires a longer running time comparedto the order of performances (2) and (3). However, the order ofperformance (1) may maximize the performance metric if a rushinstruction includes assay 1. In FIG. 11 , steps of the assays requiringresource B may be batched to minimize the total running time whileperforming the rush instruction first.

The orders of performance (2) and (3) are shown to require the samerunning time. The order of performance that maximizes the performancemetric may be the order of performance (2) if the performance metric istime-based and the assay steps that require resources A, B, and C mustbe performed consecutively. The order of performance that maximizes theperformance metric may be the order of performance (3) if theperformance metric is energy-based and resource B uses more energy thanresource C.

Determining an Updated Assays or Assay Steps Order

After the orchestration core application 220 determines an order ofperformance, the analysis system 100 may receive a new assay instructionfrom a laboratory information system 204 or a hospital informationsystem prior to the performance of the assays for the samples arecomplete. The new assay instruction may be received after or before theanalysis system 100 begins processing and analyzing the samples. FIG. 12is a block diagram of a non-limiting exemplary method 1200 ofdetermining an updated order of performance of assays or assay stepsafter receiving a new assay instruction. In one implementation, theorchestration core application 220 may implement the method 1200 or apart of the method 1200. After beginning at a block 1204, the method1200 proceeds to a block 1208, where the orchestration core application220 determines an order of performance of assays ordered for samples.The orchestration core application 220 may determine an order ofperformance of assays based on the method 1000 described with referenceto FIG. 10 .

The method 1200 proceeds to a block 1212, wherein a new assayinstruction is received. For example, the orchestration core application220 may receive a new assay instruction from a laboratory informationsystem 204 via the network 208. The new assay instruction received maybe for a new sample or an existing sample. For example, the new assayinstruction may be for an existing sample that has the analysis system100 previously received and scanned. When the new assay instruction isreceived, the analysis system 100 may be in the process of performingone or more assays already ordered for the sample, or the analysissystem 100 may be waiting for instrument devices 264, 268 to becomeavailable prior to performing the one or more assays already ordered forthe samples. As another example, the new assay instruction may be for asample 100 that has not been received and scanned.

The method 1200 proceeds to a decision block 1216 to determine whetherthe new assay instruction is for an existing sample or a new sample. Ifthe new assay instruction is for a new sample, the method 1200 proceedsto a block 1220, where the orchestration core application 220 receives anew sample identifier, such as a barcode or a two dimensional code. Forexample, the analysis system 100 may receive the new sample through theinput window 116 of the analysis system. The orchestration coreapplication 220 may receive the sample code scanned using the codescanner 304. After receiving the new sample code, the method 1200proceeds to a block 1124, where the orchestration core application 220may determine a new order of performance. The new order of performancemay be based on assays or assay steps that the analysis system 100 mayperform in light of the assays or assay steps that being currentlyperformed. Table 5 illustrates four states for assays or assay stepsthat may be performed concurrently in light of other assays or assaysteps currently being performed. The most restrictive assays or assaysteps currently being performed may affect the prospective assay orassay step. In some embodiments, the most restrictive assay or assaystep that is currently being performed determines the prospective assayor assay step that may be performed. The four states in Table 5 areordered from the least restrictive to the most restrictive. The leastrestrictive state is the most expensive, in terms of resources of theanalysis system 100, to be performed.

TABLE 5 Assays or Assay Steps Concurrency Action Description ConcurrentA prospective assay or assay step will be allowed to start regardless ofthe assay or assay step that is being performed currently. Theprospective assay or assay step may pause to acquire common resourceswhile being performed. Shutdown The assay or assay step being performedcurrently is allowed to proceed until next logical shutdown point isreach. A prospective assay or assay step will be held off until shutdownis complete. Subsequent The assay or assay step being performedcurrently will complete before a prospective assay or assay step will beallowed to start. N/A The option to start the prospective assay or assaystep should not be available while the in light of the assay or assaystep that is being performed currently.

At the decision block 1216, if the new assay instruction is for a newsample, the method 1200 proceeds to the block 1220, where theorchestration core application 220 may determine a new order ofperformance. The orchestration core application 220 may determine a neworder of performance of assays based on the method 1000 described withreference to FIG. 10 . The method ends at a block 1228. The new order ofperformance determined may be to maximize a performance metric, such asthe time or energy required to complete the assays, or the priorities ofthe assays.

In one implementation, the method 1200 may determine a new order ofperformance for the existing samples and the new sample prior toreceiving the new sample code at the block 1120. The method 1200 maycontinuously determine a new order of performance until the new samplecode is received. Thus, when the analysis system 100 receives the newsample and the method 1200 receives the new sample code, the analysissystem 100 may continue to perform assays to maximize performancewithout any time delay required to determine a new order of performance.

Determining an Order of Performance of Assays or Assay Steps

The orchestration core application 220 may determine an order ofperformance of assays or assay steps based on the samples received, theassays ordered, availabilities of resources 248, 252, and operationalstates of electronic instruments 264, 268. FIG. 13 is a flow diagram ofone exemplary method 1300 of determining an order of performance and anupdated order of performance of assays or assay steps to maximize one ormore performance metrics. In one embodiment, the orchestration coreapplication 220 may implement the method 1300 or a part of the method1300. After beginning at a block 1304, the method 1300 proceeds to ablock 1308, where the orchestration core application 220 receives assayinstructions for biological samples of one or more subjects, such aspatients. The assay instructions can include performing one or moreassays on each of one or more biological samples. For example, the assayinstructions can include performing complete blood count (CBC), bloodchemistry tests, blood enzyme tests, and blood tests to assess a heartdisease risk for a sample of a subject and performing the blood tests toassess the heart disease risk. The orchestration core application 220may receive assay instructions from an instruction provider, such as ahealthcare provider or laboratory personnel, such as a laboratorytechnician.

After receiving assay instructions, the method 1300 proceeds to a block1312, where the orchestration core application 220 determines assays tobe performed on electronic instruments 264, 268 for the biologicalsamples based on the assay instructions. Determining the assays to beperformed can comprise retrieving information relating to the assaysfrom a database of a laboratory information management system.

The method 1300 proceeds from the block 1312 to a block 1316, whereinthe orchestration core application 220 determines assay resourcesavailable and operational states of the electronic instruments 264, 268.The assay resources can include a diluent, a reagent, an assay controlsample, a pipette tip, a sample tube, an extraction tube, a polymerasechain reaction (PCR) plate, space available in a waste container, or anycombination thereof.

At a block 1320, the orchestration core application 220 can determine anorder of performance for the assays. For example, the order ofperformance can be based on the assay resources available and theoperational states of the electronic instruments 264, 268 determined atthe block 1316. The orchestration core application 220 can determine theorder of performance to maximize one or more performance metrics of theanalysis system 100. In one implementation, the orchestration coreapplication 220 can optionally receive sample scan codes to determinethe samples that have received and determine the order of performancefor the received samples.

The performance metrics for the electronic system can comprise, ordetermined based on, a number of valid assay results per time period.The number of valid assay results can be determined based on biochemicalstability of the biological sample and biochemical stability of an assayresource per time period (such as one eight-hour shift, a 24-hour timeperiod, one week, or more). For example, a performance metric can bedetermined based on the number of usable assay results per period oftime. For example, the number of valid assay results can be optimized ormaximized to ensure generation of assay results prior to the endbiochemical stability. Performing all steps of an assay are performed ona biological sample does not guarantee clinically usable result. Variousfactors can invalidate the result. For example, the orchestration coreapplication 220 may track the biochemical lifetime of inventory andsamples in various states of assay protocol execution. Exceeding theselimits of lifetime may result in indeterminate results of the assay andtherefore lower the throughput of the machine. Therefore, theorchestration core application 220 may track the viability of thepatient sample, assay controls, assay reagents, etc. These lifetimeschange as the assays are performed and the biochemistry of the samplesare altered by the assay steps. The orchestration core application 220can plan to ensure completion of all assays or assay steps once startedand before patient samples expire.

A performance metric can include the number of biological samples testedper a unit time period. For example, the primary metric can be thenumber of samples tested per period of time, such as the number ofsamples tested per day. The orchestration core application 220 canattempt to keep all analytical modules 268 and submodules and thepre-analytical modules 264 and submodules busy. The full utilization ofthese hardware resources can help the system achieve its maximumthroughput. Idle time of any module or submodule can negatively impactthe overall performance.

In one implementation, a performance metric comprises the labor or timeof laboratory personnel required to operate the analysis system 100 perunit time period. The orchestration core application 220 can track asample throughout its processing. The orchestration core application 220may track the samples across conversions to different containers andacross different modules: analytical modules, analytical submodules andthe pre-analytical module. Therefore, laboratory personnel can be freedfrom this responsibility and human error can be removed from theprocessing chain. Further laboratory personnel can query the locationand assay progress of a patient sample. If multiple assays are orderedfor a single patient sample, the orchestration can coordinate and trackthe executions of multiple assays without need for laboratory personnelto intervene. A performance metric may comprise a maximum amount of timethe electronic system requires no input of the laboratory personneland/or a minimum number of times the electronic system requires theinput of the laboratory personnel per time period. For example, theperformance metric may be determined based on the maximum time allowedbefore a user must return to the system, the minimum number of times auser must return to the system within a given period of time.

The labor required can also be determined based on a number ofinterrupts of the electronic system per time period. For example, thesecond most important metric used by the system may be the requiredlabor to operate the analysis system 100. The analysis system 100 can bedesigned to minimize the number of interrupts of a laboratory personnelper shift. By grouping the quantity of human operations together, theinterrupt of particular laboratory functions can be minimized. This isbalanced against achieving the highest throughput possible which mayrequire an operator to keep the instruments stocked and prepared formore assays.

A performance metric can be determined based on one or morepre-determined conditions, such as an urgency of an assay, a profile ofa subject, an identity of the instruction provider, or a combinationthereof. The conditions may be determined by the urgency of assaysspecified a service level agreement. For example, the urgency of anassay to be performed or test to be completed may be from a clinicalpractice perspective, such as the urgency in patient management. Asanother example, the urgency of an assay to be performed may bedetermined based on the patient profile, such as patient demographics,and statistical attributes of the assay and the subject. For example,the urgency of the assay to be performed may be affected by businessprocesses of the laboratory operating the system and the need to fulfillservice level agreements between the laboratory and instructionproviders, such as laboratory customers. As another example, thecondition may be an one-time event, such as a sample is temporarilymisplaced by laboratory personnel.

In one embodiment, the performance metrics comprise a weighted matrixwith the number of valid assay results per unit time period, the numberof biological samples tested per unit time period, the labor required tooperate the electronic system per unit time period, and/or othervariables or factors disclosed herein, weighted in ascending order ordescending order. In one embodiment, the performance metrics comprises ametric corresponding to the duration of an assay, priority of abiological sample, biochemical stability of each biological sample,state of the electronic instrument, concurrency of the plurality ofassay resources required for performing the plurality of assays, or anycombination thereof. In another embodiment, the performance metricsreflects predetermined guidelines for the samples and assays. Forexample, an assay order may include parameters such as result urgency,sample expiration, user defined parameters, etc. The performance metricscan reflect such parameters. Laboratory personnel can change thepriority of an individual sample or a group of samples to be processed.

Determining the order of performance can comprise determining the orderof performance for the one or more assays based on the available assayresources. The orchestration core application can consider inventoriesavailable, operational states of the hardware components, patientordered assays, samples availability, sample age, batches already inprocess, availability of analytical modules, analytical submodules andthe pre-analytical module, biochemical stability and/or laboratorybusiness practices. Efficient orchestration can minimize consumableexpenditures, idle analytical modules, analytical submodules and thepre-analytical module, and indeterminate results.

Determining the order of performance can comprise organizing theplurality of biological samples into a plurality of sample batches. Theelectronic instrument can be configured to process a batch of samples atthe same time. An assay resource can be configured for the electronicinstrument to process the batch of samples at the same time. Forexample, thermocycling performance requires like assays because allsamples are exposed to the same temperature variations and frequencies.Therefore, samples can be organized into batches. The consumables andthe instrument devices 264, 268 can be designed to process samples indiscrete batch sizes per assay. For example, the instrument devices 264,268 can be designed to process 96 samples in a 96-well plate format.Thus, to maximize the overall throughput, each patch for an assay shouldinclude 96 samples.

At a block 1324, the orchestration core application 220 can allocateassay resources to the assays to be performed. The orchestration coreapplication 220 can track the assay resources available and notifylaboratory personnel when an assay resource is unavailable or isexpected to be unavailable. For example, the orchestration coreapplication 220 can track current level of consumable inventory in eachanalytical module and the pre-analytical module. The orchestration coreapplication 220 knows the quantity already allocated to batches inprocess. It knows the quantities of consumable inventory required for abatch of each assay type. This knowledge allows the orchestration coreapplication 220 to make decisions about which samples should beprocessed and when to start.

After allocating the assay resources, the method 1300 can proceed to ablock 1328, where the orchestration core application 220 can configurethe electronic instruments 264, 268 based on the order of performancedetermined at block 1320. For example, the orchestration coreapplication 220 can schedule the electronic instruments 264, 268 toperform the assays based on the order of performance determined at theblock 1320.

At block 1332, the analysis system 100 can perform the assays on thebiological samples using the electronic instruments configured based onthe order of performance. The orchestration core application 220 cankeep track of the operational states of the electronic instruments 264,268 while performing the assays. Modular assay instruments are complexmachines. The electrical, mechanical and pneumatic systems may fail. Toachieve the highest sample per day metric, the orchestration coreapplication 220 can monitor equipment health and adapts the execution ofassay to the operational hardware. For example, the orchestration coreapplication 220 can monitor operational states of the electronicinstruments 264, 268. The operational states of the electronicinstruments 264, 268 can include a failed status, an offline status, anonline status, a paused status, a power off status, a busy status, anidle status, or any combination thereof. When the orchestration coreapplication 220 determines or receives an indication that theoperational status of one of the electronic instruments 264, 268 is thefailed status, the orchestration core application 220 can notifylaboratory personnel of the failed status.

Alternatively or additionally, the orchestration core application 220can notify laboratory personnel when and what to restock in the analysissystem 100. Inventory items include diluents, reagents, assay controlsamples, pipette tips, sample tubes, extraction tubes and PCR plates.The resources available can include space available in the various wastecontainers.

At a decision block 1336, if the operational state of one of theelectronic instruments 264, 268 is the failed status, the method 1300proceeds to the block 1340, where the orchestration core application 220deallocates assay resources allocated for performing assays that havenot been completed. After deallocating the assay resources, the method1300 proceeds to the block 1316, where the orchestration coreapplication 220 can determine the updated assay resources available andthe updated operational states of the electronic instruments 264, 268,including the unavailable operational state of one of the electronicinstruments 264, 268, at the block 1316 and determine an updated orderof performance of the incomplete assays based on the updated assayresources available and the updated operational states of the electronicinstruments 265, 268. In one embodiment, the orchestration coreapplication 220 continuously determines an updated order of performanceand de-allocates and allocates resources. The updated order ofperformance can be based on the operational states of the electronicinstruments 264, 268, the resources available, and new assayinstructions and new samples received.

If the operational states of the electronic instruments 264, 268 duringthe performance of the assays do not include the failed status, theanalysis system 100 can continue performing the assays on the biologicalsamples until all assays or assay steps are completed, where the method1300 ends at a block 1344.

FIG. 14 is a flow diagram of one exemplary method 1400 of determining anorder of performance and an updated order of performance of assays orassay steps to maximize one or more performance metrics. In oneembodiment, the orchestration core application 220 may implement themethod 1400 or a part of the method 1400. After beginning at block 1404,the method 1400 may proceed to blocks 1408, 1412, 1416, 1420, 1424,1428, and 1432 as described with reference to blocks 1308, 1312, 1316,1320, 1324, 1328, and 1332.

At a decision block 1436, the orchestration core application maydetermine that an assay on a sample is no longer required. Then method1400 may proceed to a block 1440, where the orchestration coreapplication deallocates assay resources allocated for performing assaysthat have not been completed as described with reference to block 1340in FIG. 13 . For example, the orchestration core application may receivea result of an assay on a biological sample determined using one or moreof the electronic instruments using the ordered determined. Theorchestration core application can determine a second assay of thebiological same or another biological sample needs not be performed. Forexample, a unit of work, which may include one or more assays, can becancelled due to inferred results from a prior assay result. Suchcancellation may result in cost savings or time sayings since thesecond/pending assay no longer needs to be performed. The orchestrationcore application may determine that a pending assay is no longerrelevant to a clinical diagnosis via a set of rules. For example, afirst cheaper assay for determining a physiological condition or statemay have a low false positive rate and a high false negative rate, and asecond more expensive assay for determining the same physiologicalcondition may have a low false positive rate and a low false negativerate. Instructions received by the orchestration may include performingboth assays for a sample, and the orchestration core application maydetermine that the first assay should be performed before the secondassay is performed. If the result of the first assay is negative, thesecond assay may be performed. If the result of the first assay ispositive, the orchestration core application may determine that thesecond assay needs not be performed. The orchestration core applicationcan determine an updated order of performance, which excludes performingthe second assay on the sample, to maximize at least one performancemetric of the analysis system. Resources may be deallocated based on theupdated order of performance.

If all assays are required, the analysis system can continue performingthe assays on the biological samples until all assays or assay steps arecompleted, where the method 1400 ends at a block 1444.

Additional Features

Storing of Assay Results. The analysis system 100 or 100A may performassays based on an assay order received from the laboratory informationsystem and an order of performance determined by the orchestration coreapplication. Although the modules listed below relate to the analysissystem 100 shown in FIG. 2A, these same assays may be performedsimilarly by the analysis system 100A of FIG. 2B. After completion ofthe assays, the analysis system 100 can send the assay results to thelaboratory information system 204 via the network 208. Due to network orother problems, the analysis system 100 may be unable to establish aconnection with the laboratory information system 204 via the network208 when the assay results are available. In this embodiment, theanalysis system 100 can store assay results locally and then send theresults to the laboratory information system 204 once a connection isestablished. The analysis system 100 can attempt to reestablish aconnection periodically. If no connection can be reestablished,laboratory personnel can be notified of the failed status. Thisnotification may be, for example, an email, text, sound or otherindication that the results were not sent to the laboratory informationsystem 204. The analysis system 100 can store the assay results in anunencrypted format or an encrypted format using symmetric-key schemes.

Monitoring of Inventory and Operational Integrity.

The orchestration core application 220 may determine an order ofperformance of assays or assay steps based on the samples received, theassays ordered, availabilities of resources 248, 252, and operationalstates of electronic instruments 264, 268. The orchestration coreapplication 220, the orchestration sub-application 240 of thepre-analytical instrument 104, or the orchestration sub-application 244of the analytical instruction 108 may keep track of assay resourcesavailable. The assay resources may include consumables 256, 268 andreagents 272, 276. The assay resources can include a diluent, a reagent,an assay control sample, a pipette tip, a sample tube, an extractiontube, a polymerase chain reaction (PCR) plate, space available in awaste container, or any combination thereof.

Modular assay instruments are complex machines. The electrical,mechanical and pneumatic systems may fail. To achieve the highestperformance, the orchestration core application 220 can monitor theequipment health and integrity of the electronic instruments 264, 268and adapt the execution of each assay being performed to the operationalhardware. For example, the orchestration core application 220 canmonitor operational states of the electronic instruments 264, 268. Theoperational states of the electronic instruments 264, 268 may include afailed status, an offline status, an online status, a paused status, apower off status, a busy status, an idle status, or any combinationthereof. As another example, the analysis system 100 can include anexternally or internally mounted un-interruptible power supply (UPS).The orchestration core application 200 may monitor the health of theUPS. When the orchestration core application 220 determines or receivesan indication that the operational status of one of the electronicinstruments 264, 268 is the failed status, the orchestration coreapplication 220 can notify laboratory personnel of the failed status.

The analysis system 100 can generate a report of the inventory and theoperational integrity of the electronic instruments 264, 268. Forexample, when the orchestration core application 220 determines that acomponent of an electronic instrument 264, 268 has a failed status, theanalysis system 100 can generate a report with diagnostic data and codesindicating that the particular component has failed and needs to beserviced or replaced. The orchestration core application 220 canre-determine an order of performance based on the failure. Some assaysmay be paused and restarted while other assays may be repeated.

The orchestration core application 220 can coordinate the operations ofmultiple independent, but connected, instruments that requireavailability of hardware and consumables across these instruments tocorrectly prepare and analyze a single sample. The independent andconnected instruments may include the pre-analytical instrument 104, theanalytical instrument 108, and the instrument devices 264, 268. Forexample, to perform an assay on a sample, the sample may have to bepipetted. If any of the pipette robots or pipette tips of thepre-analytical instrument 104 or the consumables 268 and reagents 276 ofthe analytical instrument 108 are not available, the orchestration coreapplication 220 may determine an order of performance to exclude theassay being performed on the sample.

Status Indicators.

The analysis system 100 can include multiple visual indicators acrossmultiple independent but connected instruments. The analysis system 100can use the visual indicators to indicate to users of the system 100that user attention is needed by the system 100. For example, a visualindicator associated with the analysis system 100 may flash red whenthere is an overall system failure. As another example, an indicatorassociated with the pre-analytical system 104 may flash yellow whenconsumables 256, such as pipette tips, need to be refilled soon.

Log.

The analysis system 100 may aggregate and store log files of themultiple independent but connected instruments for later retrieval. Forexample, the analysis system 100 may aggregate and store log files ofthe assays performed, the operational states of the instruments 104, 108and devices 264, 268, and the levels of the consumables 256, 268 andreagents 272, 276. As another example, the log files can include resultsor intermediate results of the assays being performed. The analysissystem 100 may transfer the log file data to a central or remote datastorage device to allow remote troubleshooting via analysis of the logs.For example, when a component of the pre-analytical instrument 104 has afailed status, the analysis system 100 can retrieve a log filecontaining such failed status from the pre-analytical instrument 104 andtransfer the log file to the laboratory information system 204 fordiagnosis of the failed status. The log file information may betransferred based on the importance or the timing of the log fileinformation. For example, log file information containing a failedstatus of the overall analysis system 100 may be prioritized over logfile information indicating that consumables should be refilled soon.

Determining Operating Coordinates and Parameters.

The instrument devices 264, 268 may include physical hardware componentssuch as motor encoders, integrated circuits, solenoids, and the like sothe orchestration core application 220 is able to track the operationalstate of the hardware in each instrument. In one implementation, theinstrument devices 264, 268 may include interactive position probes andcameras, and the orchestration core application 220 can determinecorrect operating coordinates and parameters of the instrument devices264, 268 or components thereof. For example, the pre-analyticalinstrument 104 may include a pipette robot with a position probe. Thepre-analytical instrument 104 may include a camera that captures imagesof the position probe. The orchestration core application 220 candetermine the coordinates and the parameters of the pipette robot usingthe images of position probe. As another example, the pipette robot caninclude multiple position probes and the pre-analytical instrument 104can include three cameras that are orthogonal to one another. Theorchestration core application 220 can determine the coordinates and theparameters of the pipette robot in three dimensions using the imagescaptured by the orthogonal camera. The images captured may also be usedto calibrate the components of the instrument devices 264, 268. Theposition probes may be fixed or movable on the components. Fewer movableposition probes may be need to determine the operating coordinates andparameters of the components. The position probes may use differentcolors to indicate its status, such as in use or failed.

Un-Interruptible Power Supply.

The analysis system 100, the pre-analytical instrument 104, theanalytical instrument 108, or the instrument devices 264, 268 mayinclude an externally or internally mounted un-interruptible powersupply (UPS). In the event of a power failure, the UPS may provide theanalysis system 100 or its components sufficient power to ensure thatall data is stored to a durable storage device, such as a Solid StateDrive (SSD) or Hard Disk Drive (HDD). The data stored to the durablestorage device in the event of power failure can include results orintermediate results of the assays being performed. The data may includestates and parameters of the analysis system 100 and its components.

Video Surveillance.

The analysis system 100 can include internal cameras that capture videosurveillance data of the inner workings of the system 100. The analysissystem 100 may store the video surveillance data and display the videoon demand to a user or technician of the system 100. In one embodiment,the video surveillance data is stored in a durable internal storagedevice for later retrieval.

For example, laboratory personnel, or a technician, may want to review avideo captured when a failed status of a component of the analysissystem 100 is detected. As another example, laboratory personnel maywant to review a video tracking a sample of interest to ensure that notampering occurred with the sample. The analysis system 100 mayautomatically package the video with logs and other data to supportremote evaluation of errors or issues.

Coordinating with Other Computer Systems or Sub-Systems.

In one embodiment, the orchestration core application 220 can coordinatewith other systems associated with the analysis system 100. For example,the orchestration core application 220 can determine an order ofperformance based on the operational states of the pre-analyticalinstrument 104 and the analytical instrument 108. As another example,the orchestration core application 220 of one analysis system 100 candetermine an order of performance based on the operational state ofanother analysis system 100. In one embodiment, the orchestrationsub-application 240 of the pre-analytical instrument 104 can affect theorder of performance determined by the orchestration core application220 for the pre-analytical instrument 104 and the analytical instrument108, and vice versa.

Worklists of Samples.

The orchestration core application 220 may automatically build andrelease worklists of samples for processing as groups of samples presentthat correspond to the nominal operation of the analysis system 100 orits components. For example, the orchestration core application 200 mayautomatically build and release worklists of samples for processing asgroups of samples present that correspond to the nominal operation ofthe device and according to user defined rules based on day of the week,day of the month, time of day, or any combination of the above. Asanother example, the orchestration core application 220 mayautomatically build and release worklists of samples present forprocessing as groups of samples that correspond to the nominal operationof the device and according to user defined rules based on day of theweek, day of the month, time of day, or any combination of the above asapplied to a specific test that has been order for each sample.

Sample Removal.

The orchestration core application 220 can monitor the processing andanalysis of a sample and alert laboratory personnel when the originalsample container that is being removed or has already been removed bythe laboratory personnel should be retrieved for further review andevaluation. For example, the orchestration core application may alertthe user when the original sample container that has already beenremoved from the system should be retrieved for further review andevaluation and provide the laboratory personnel sample information andlocation for ease sample retrieval. The sample information and locationmay include a sample identifier and a location of the sample, such as alocation on a rack. The orchestration core application 220 canre-determine an order of performance when the sample is returned to theanalysis system 100.

Cloud-Based Orchestration Core Application

FIG. 15 is a block diagram of an analysis system in communication with alaboratory information system and analysis systems over a network. Ahospital 1504 a may include a hospital information system 1508 a thatstores and processes hospital data. For example, the hospitalinformation system 1508 a may store patient data and prescriptionordering information. The hospital 1504 a may also have an onsitehospital laboratory 1512 a with a laboratory information system 204 aand an analysis system 100 a. The laboratory information system 204 amay receive assay instructions 212 and patient information from thehospital information system 1508 a. The laboratory information system204 a may store the requirements of the assays that the analysis system100 a is capable of performing. The analysis system 100 a may be capableof performing certain assays such as a general cancer panel. Althoughthe orchestration core application 220 is shown to control two analysissystems, the orchestration core application 220 is capable ofcontrolling numerous analysis systems with different capabilitiessituated at different geographical locations. The analysis systems 100a, 100 b may be the analysis system of FIG. 2A and/or FIG. 2B.

A laboratory 1512 b, such as an independent laboratory, may include alaboratory information system 204 b and an analysis system 100 b. Thelaboratory information system 204 b may store the requirements of theassays that the analysis system 100 a is capable of performing. Thecapability of the analysis system 100 b and the capability of theanalysis system 100 a may be the same or different. For example, theanalysis system 100 b of the laboratory 1512 b may be capable ofperforming a general cancer panel and a specialized cancer instruction.

To determine an order of performance for the analysis system 100 a orthe analysis system 100 b, the orchestration core application 220 mayreceive assay instructions from the hospital information system 1508 a,the laboratory information system 204 a, or the laboratory informationsystem 204 b. The orchestration core computing application 220 may keeptrack of the capabilities of the analysis systems 100 a, 100 b. Forexample, a resource of the analysis system 100 a may become temporarilyavailable, and the analysis system 100 a may provide the orchestrationcore application 220 with this information.

Given the assay instructions received or the samples scanned, theorchestration core application 220 may determine orders of performancefor the analysis systems 100 a, 100 b, to maximize a performance metric.For example, the hospital 1204 a may prefer that its analysis system 100a performs as many assays as possible in order to minimize cost.However, depending on the availability and capability of the analysissystem 100 a, the orchestration core application 220 may determine thatcertain assays or certain assays for certain samples should be performedby the analysis system 100 b.

As another example, an assay instruction may state that a specializedcancer panel should be performed after a general cancer panel determinesthat a patient is at risk of a cancer. The initial orders of performancefor the analysis systems 100 a, 100 b determined by the orchestrationcore application 220 may include the general cancer panel beingperformed by the analysis system 100 a of the hospital 1504 a. Theorders of performance for the analysis systems 100 a, 100 b may bedetermined using the methods 1000 and 1200 described with reference toFIGS. 10 and 12 respectively. If the result of the general cancer panelindicates that the patient at risk of a cancer, the orchestration coreapplication 220 may determine a new order of performance for theanalysis system 100 c of the laboratory 1512 b. This new order ofperformance may take into account of the time required to transport thesample from the hospital 1504 a to the laboratory 1512 b. Theorchestration core application 220 may determine the new order ofperformance using the methods 1000 and 1200 described with reference toFIGS. 10 and 12 respectively. For example, the analysis system 100 b maybe performing assays for other samples when the result of the generalcancer panel becomes available. The new order of performance for theanalysis system 100 c may be determined to maximize the performance ofthe analysis system 100 c or the combined performance of the analysissystems 100 a, 100 b.

In one embodiment, the orchestration core application 220 may receive anindication that the analysis system 100 b becomes unavailable. Theanalysis system 100 b may become unavailable if the connection of theorchestration core application 220 to the analysis system 100 b is lostor performing a rush assay instruction. Based on the unavailability ofthe analysis system 100 b, the orchestration core application 220 maydetermine a new order of performance for the analysis system 100 a. Inone embodiment, the orchestration core application 220 determines ordersof performance for some analysis systems in order to maximize aperformance metric with respect to these analysis systems to increasethe overall efficiency of handling assay samples. For example, thehospital 1504 a may have a contractual relationship with the laboratory1512 b such that orders of performance for analysis systems 100 a, 100 bare determined to maximize a performance metric with respect to thesetwo analysis systems 100 a, 100 b.

FIG. 16 is a schematic illustration of an orchestration core applicationstored in a cloud-based server in communication with an orchestrationlaboratory application to coordinate automated sample processing andanalysis. A hospital 1504 may include a hospital information system 1508that stores and processes hospital data. For example, the hospitalinformation system 1508 may store patient data and prescription orderinginformation. The hospital 150 a may have an onsite hospital laboratory1512 with a laboratory information system 204 and multiple analysissystems 100 a, 100 b. The laboratory information system 204 may receiveassay instructions and patient information from the hospital informationsystem 1508. The laboratory information system 204 may store therequirements of the assays that the analysis systems 100 a, 100 b arecapable of performing.

An orchestration core application 220 on a cloud system 1600 cancommunication with an orchestration laboratory application 1604 on thelaboratory information system 204 to coordinate automated sampleprocessing and analysis using the analysis systems 100 a, 100 b. Whenthe orchestration core application 220 is available, the orchestrationlaboratory application 1604 may send the assay instructions received orthe samples scanned to the orchestration core application 220. Based onthe information received from the orchestration laboratory application1604 and similar information received from other orchestrationlaboratory application, the orchestration core application 220 maydetermine orders of performance for the analysis systems 100 a, 100 bcontrolled by the orchestration laboratory application 1604 and analysissystems controlled by other orchestration laboratory systems.Consequently, the orders of performance determined by the orchestrationcore application 220 can maximize a performance metric given the assayinstructions received or the samples scanned. When the orchestrationcore application 220 is unavailable, the orchestration laboratoryapplication 1604 may be capable of determining orders of performance forthe analysis systems 100 a, 100 b, to maximize a performance metricgiven the assay instructions received or the samples scanned.

With this distributed architecture, the orchestration core application220 and the orchestration laboratory application 1604 may maximize aperformance metric given the information and resources available. Forexample, orders of performance determined by the orchestration coreapplication 220 may be based on the capabilities of the analysis systems100 a, 100 b in the laboratory 1512 and another laboratory. Eachlaboratory has an analysis system capable of performing a general cancerpanel. However, performing the general cancer panel using the analysissystem in the laboratory 1512 may be more costly. To reduce the cost ofperforming the cancer panel, the orchestration core application 220 maydetermine that the general cancer panel been performed using an analysissystem of the other laboratory. Prior to the sample (or a portion of thesample) for the cancer panel is sent to the other laboratory, theorchestration laboratory application 1604 may lose its connection to theorchestration core application 220. Because the orchestration laboratoryapplication 1604 is uncertain of whether the general cancer panel can becompleted even if the sample (or a portion of the sample) is sent to theother laboratory, the orchestration laboratory application 1604 candetermine a new order of performance for the analysis systems 100 a, 100b.

In one embodiment, the cloud system 1600 may, via its orchestration coreapplication 220, receive data or test results generated by the analysissystems 100 a, 100 b, from the orchestration laboratory application1604. Although the orchestration core application 220 is shown tocontrol two analysis systems 100 a, 100 b, the orchestration coreapplication 220 is capable of controlling numerous analysis systems withdifferent capabilities situated at different geographical locations.

The laboratory 1512 may include a number of legacy systems 1608 withoutautomation capability. These legacy systems 1608 can be controlled bylab-based middleware systems providing the high availability and highperformance link between the lab platforms, and the other IT systems.This may be used primarily for running the local laboratory operations.The cloud system 1600 may, via its legacy system interface 1612, receivedata or test results generated by these legacy systems 1608 from alegacy system laboratory interface 1616 of the laboratory informationsystem 204. The legacy system laboratory interface 1616 may receive datagenerated by the legacy systems 1608 from lab-based middleware systems.In one embodiment, the cloud system 1600 may receive data or testresults generated by point-of-care (POC) devices via a POC interface.

By controlling analysis systems 100 a, 100 b and receiving data and testresults generated by the analysis systems 100 a, 100 b, the legacysystems 1608, and POC devices 1615, the cloud system 1600 is capable ofenterprise-wide management of related laboratory data as well as remotemicrobiology operations for labs. Aggregation of data across allhospitals, laboratories, and patients enables value-added services andprovides insight to hospital, laboratory, and patients usages. Examplesof value-added services include peer benchmarking and globalsurveillance. The data and test results received can be stored in a datamart capable of global clinical and diagnostic aggregation. In oneembodiment, data for different hospitals, institutions, or affiliatedhospitals or institutions are stored in different databases 1624 a, 1624b at different locations 1632 a-1632 e.

Access to the cloud functionality may be provided via Apps 1636distributed through an application portal 1640, supporting bothtraditional and mobile devices. The application portal 1640 may becentrally managed and redirect users to the relevant technology-specificApp stores. These App stores may enable distribution of Apps 1636,possibly developed by third-party developers, that are in compliancewith the architecture of the cloud system 1600. Apps 1636, possiblydeveloped by third-party develops, may more flexibly address custom datamanagement requirements.

In one embodiment, the cloud system 1600 takes advantage of socialnetworking to enable better engagement of hospitals, laboratories, andpatients. The cloud system 1600 may provide better Customer RelationshipManagement activities ranging from service and training to opportunitiesfor inbound and outbound marketing activities.

The architecture of the cloud system 1600 is scalable to meet changingmarket demands. In one embodiment, the architecture supports both publicand local (private) clouds, which eliminate data sovereignty objectionsfor users that want all data behind their firewall. The cloud system1600 is secure, thus addressing concerns regarding data, and HIPAAprivacy, and regulatory compliance. The cloud system 1600 is alsoextensible and capable of supporting new/updated devices and modules.

In at least some of the previously described embodiments, one or moreelements used in an embodiment can interchangeably be used in anotherembodiment unless such a replacement is not technically feasible. Itwill be appreciated by those skilled in the art that various otheromissions, additions and modifications may be made to the methods andstructures described above without departing from the scope of theclaimed subject matter. All such modifications and changes are intendedto fall within the scope of the subject matter, as defined by theappended claims.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity. As used in this specification and the appended claims, thesingular forms “a,” “an,” and “the” include plural references unless thecontext clearly dictates otherwise. Any reference to “or” herein isintended to encompass “and/or” unless otherwise stated.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to embodiments containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should be interpreted to mean “at least one”or “one or more”); the same holds true for the use of definite articlesused to introduce claim recitations. In addition, even if a specificnumber of an introduced claim recitation is explicitly recited, thoseskilled in the art will recognize that such recitation should beinterpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, means at leasttwo recitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,etc.” is used, in general such a construction is intended in the senseone having skill in the art would understand the convention (e.g., “asystem having at least one of A, B, and C” would include but not belimited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those withinthe art that virtually any disjunctive word and/or phrase presenting twoor more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are describedin terms of Markush groups, those skilled in the art will recognize thatthe disclosure is also thereby described in terms of any individualmember or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and allpurposes, such as in terms of providing a written description, allranges disclosed herein also encompass any and all possible sub-rangesand combinations of sub-ranges thereof. Any listed range can be easilyrecognized as sufficiently describing and enabling the same range beingbroken down into at least equal halves, thirds, quarters, fifths,tenths, etc. As a non-limiting example, each range discussed herein canbe readily broken down into a lower third, middle third and upper third,etc. As will also be understood by one skilled in the art all languagesuch as “up to,” “at least,” “greater than,” “less than,” and the likeinclude the number recited and refer to ranges which can be subsequentlybroken down into sub-ranges as discussed above. Finally, as will beunderstood by one skilled in the art, a range includes each individualmember. Thus, for example, a group having 1-3 articles refers to groupshaving 1, 2, or 3 articles. Similarly, a group having 1-5 articlesrefers to groups having 1, 2, 3, 4, or 5 articles, and so forth.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. An electronic system for analyzing a plurality ofbiological samples using a plurality of electronic instruments,comprising: a plurality of electronic instruments comprising a pluralityof analytical modules and associated analytical submodules and aplurality of pre-analytical modules and associated pre-analyticalsubmodules; a memory storing assay resources available, assay resourcesrequired for a plurality of assays, and performance metrics for theelectronic system; and a processor programmed to execute a methodcomprising: receiving a plurality of assay instructions for a pluralityof biological samples of at least one subject from an instructionprovider; determining one or more assays to be performed on eachelectronic instrument for each biological sample based on the assayinstructions; determining the assay resources available and operationalstates of the plurality of electronic instruments; determining an orderof performance for the one or more assays, based on the assay resourcesavailable and the operational states of the plurality of electronicinstruments, to maximize at least one performance metric for theelectronic system; allocating assay resources of the assay resourcesavailable to the one or more assays to be performed; configuring each ofthe plurality of electronic instruments based on the order ofperformance; and performing the one or more assays on the plurality ofbiological samples using the configured plurality of electronicinstruments in the determined order.
 2. The electronic system of claim1, wherein the performance metrics for the electronic system comprises aperformance metric related to a number of valid assay results per timeperiod, a number of biological samples tested per time period, or acombination thereof.
 3. The electronic system of claim 2, wherein thenumber of valid assay results is determined based on biochemicalstability of the biological sample and biochemical stability of an assayresource.
 4. The electronic system of claim 2, wherein the performancemetrics for the electronic system further comprises a performance metricrelated to time of laboratory personnel required to operate theelectronic system per time period, a maximum amount of time theelectronic system requires no input of the laboratory personnel, aminimum number of times the electronic system requires the input of thelaboratory personnel per time period, or a combination thereof.
 5. Theelectronic system of claim 4, wherein the user time required isdetermined based on a number of interrupts of the electronic system pertime period.
 6. The electronic system of claim 2, wherein the timeperiod comprises a 24-hour time period.
 7. The electronic system ofclaim 1, wherein the performance metrics for the electronic systemcomprise a performance metric related to consumable expendituresrequired to complete the one or more assays.
 8. The electronic system ofclaim 1, wherein the performance metrics for the electronic systemcomprise a performance metric related to one or more pre-determinedconditions.
 9. The electronic system of claim 8, wherein the one or morepre- determined conditions comprises an urgency of an assay, a profileof the at least one subject, an identity of the instruction provider, ora combination thereof.
 10. The electronic system of claim 1, whereindetermining the order of performance comprises determining the order ofperformance for the one or more assays based on the available assayresources.
 11. The electronic system of claim 1, wherein determining theorder of performance comprises organizing the plurality of biologicalsamples into a plurality of sample batches.
 12. The electronic system ofclaim 11, wherein the electronic instrument is configured to process abatch of samples at the same time.
 13. The electronic system of claim12, wherein an assay resource is configured for the electronicinstrument to process the batch of samples at the same time.
 14. Theelectronic system of claim 1, wherein determining the one or more assaysto be performed comprises retrieving information relating to the one ormore assays from a database of a laboratory information managementsystem.
 15. The electronic system of claim 1, wherein the processor isfurther programmed to execute a method comprising: monitoring anoperational state of the electronic instrument, wherein the operationalstate comprises a failed status; notifying laboratory personnel of thefailed status; and determining an updated order of performance for theone or more assays to maximize at least one performance metric of theelectronic system.
 16. The electronic system of claim 15, wherein the atleast one performance metric used in determining the order ofperformance and the at least one performance metric used in determiningthe updated order of performance are identical.
 17. The electronicsystem of claim 15, wherein determining the updated order of performancecomprises: deallocating the assay resources for performing the one ormore assays that have not been performed; updating assay resourcesavailable after deallocating the assay resources for performing the oneor more assays; and determining the updated order of performance for theone or more assays, based on the updated assay resources available andthe operational states of the electronic instrument, to maximize the atleast one performance metric for the electronic system.
 18. Theelectronic system of claim 1, wherein the processor is furtherprogrammed to execute a method comprising: receiving a result of a firstassay of the one or more assays on a biological sample of the pluralityof biological samples determined using one or more of the configuredplurality of electronic instruments in the determined order; determininga second assay of the one or more assays on the biological sample needsnot be performed; and determining an updated order of performance forthe one or more assays to maximize at least one performance metric ofthe electronic system.
 19. The electronic system of claim 1, wherein theprocessor is further programmed to execute a method comprising: trackingthe assay resources available; and notifying laboratory personnel whenan assay resource is unavailable or is expected to be unavailable.
 20. Amethod for high throughput automation of biological assays on aplurality of electronic instruments, comprising: receiving a pluralityof assay instructions for a plurality of biological samples; determiningone or more assays to be performed on each electronic instrument of aplurality of electronic instruments for each biological sample based onthe assay instructions; determining the assay resources available andstates of the plurality of electronic instruments; determining an orderof performance for the one or more assays, based on the assay resourcesavailable and the states of the plurality of electronic instruments, tomaximize at least one performance metric for the electronic system;configuring each of the plurality of electronic instruments based on theorder of performance; and performing the one or more assays on theplurality of biological samples using the configured plurality ofelectronic instruments in the determined order, wherein the plurality ofelectronic instruments comprises a plurality of analytical modules andassociated analytical submodules and a plurality of pre-analyticalmodules and associated pre-analytical submodules.
 21. The method ofclaim 20, wherein the performance metrics for the electronic systemcomprises performance metrics for each electronic instrument of theplurality of electronic instruments, and wherein the target performancemetric for the electronic system comprises a target performance metricfor each electronic instrument to perform the one or more assays. 22.The method of claim 21, wherein the performance metrics for eachelectronic instrument comprises an amount of idle time per time period.23. The method of claim 20, wherein the performance metric for theelectronic system comprises a metric for a duration of an assay,priority of a biological sample, a biochemical stability of eachbiological sample, a state of the electronic instrument, concurrency ofthe plurality of assay resources required for performing the pluralityof assays, or any combination thereof.
 24. The method of claim 20,wherein the assay resources comprise a diluent, a reagent, an assaycontrol sample, a pipette tip, a sample tube, an extraction tube, apolymerase chain reaction (PCR) plate, space available in a wastecontainer, or any combination thereof.
 25. The method of claim 20,wherein determining the order of performance for the one or more assayscomprises allocating assay resources to the one or more assays to beperformed.
 26. An electronic system for analyzing a plurality ofbiological samples using a plurality of electronic instruments,comprising: a memory storing assay resources and performance metricsassociated with each electronic instrument in the plurality ofelectronic instruments; a database of assays to be performed for abiological sample; a database of available electronic instruments incommunication with the electronic system, wherein the database comprisesassay resources available for each electronic instrument; an order ofperformance for carrying out each of the assays on the biological sampleand an identification of the electronic instrument scheduled to performthe assays; an interface configured to transmit operating instructionsto a first electronic instrument listed in the order of performance toperform a first assay; and a processor programmed to execute a methodcomprising: monitoring the first electronic instrument to determine whenthe first assay has completed; instructing a second electronicinstrument to perform a second assay for the biological sample; andupdating the performance schedule in the electronic system to indicatethat a second assay has begun.
 27. An electronic system for highthroughput automation of biological assays, comprising: a memory storinginstructions; and a processor programmed by the instructions to executea method comprising: receiving a plurality of assay instructions for aplurality of biological samples from a plurality of analysis systems;determining the plurality of assays that need to performed for eachsample in the plurality of biological samples based on the assayinstructions; identifying the analysis systems available to run eachtype of assay in the plurality of assays; determining the assayresources within the identified analysis systems that are available toperform the plurality of assays; determining an order to perform eachassay in the plurality of assays based on the assay resources that areavailable in order to maximize the efficiency of performing theplurality of assays; and instructing one or more analysis systems tocarry out specific assays of the plurality of assays based on thedetermined order.
 28. The electronic system of claim 27, wherein theprocessor is programmed to perform a method that further comprises:determining the assay location of a first biological sample in theplurality of biological samples; comparing the analysis systemsavailable at the assay location with the plurality of assays to be runat the assay location; and initiating transportation of the firstbiological sample from the assay location of the first biological sampleto a second assay location.